{"id":13408227,"url":"https://github.com/benedekrozemberczki/awesome-decision-tree-papers","last_synced_at":"2025-05-15T08:05:05.995Z","repository":{"id":43343578,"uuid":"186166778","full_name":"benedekrozemberczki/awesome-decision-tree-papers","owner":"benedekrozemberczki","description":"A collection of research papers on decision, classification and regression trees with implementations.","archived":false,"fork":false,"pushed_at":"2024-03-16T21:14:33.000Z","size":891,"stargazers_count":2399,"open_issues_count":1,"forks_count":343,"subscribers_count":129,"default_branch":"master","last_synced_at":"2025-05-07T22:02:04.336Z","etag":null,"topics":["cart","catboost","classification-model","classification-trees","classifier","decision-tree","decision-tree-classifier","decision-tree-learning","decision-tree-model","ensemble-learning","gradient-boosting","gradient-boosting-machine","lightgbm","machine-learning","machine-learning-research","random-forest","regression-tree","statistical-learning","tree-ensemble","xgboost"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"cc0-1.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/benedekrozemberczki.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":".github/FUNDING.yml","license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null},"funding":{"github":["benedekrozemberczki"]}},"created_at":"2019-05-11T18:14:03.000Z","updated_at":"2025-04-29T10:05:43.000Z","dependencies_parsed_at":"2024-04-13T22:51:48.745Z","dependency_job_id":"f456298d-c546-4e47-9ae8-2ab9c3b79b57","html_url":"https://github.com/benedekrozemberczki/awesome-decision-tree-papers","commit_stats":{"total_commits":276,"total_committers":4,"mean_commits":69.0,"dds":"0.018115942028985477","last_synced_commit":"5dcbe58f77f112ef8b5ad32531998b0da819f261"},"previous_names":[],"tags_count":4,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benedekrozemberczki%2Fawesome-decision-tree-papers","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benedekrozemberczki%2Fawesome-decision-tree-papers/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benedekrozemberczki%2Fawesome-decision-tree-papers/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benedekrozemberczki%2Fawesome-decision-tree-papers/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/benedekrozemberczki","download_url":"https://codeload.github.com/benedekrozemberczki/awesome-decision-tree-papers/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":254301422,"owners_count":22047901,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["cart","catboost","classification-model","classification-trees","classifier","decision-tree","decision-tree-classifier","decision-tree-learning","decision-tree-model","ensemble-learning","gradient-boosting","gradient-boosting-machine","lightgbm","machine-learning","machine-learning-research","random-forest","regression-tree","statistical-learning","tree-ensemble","xgboost"],"created_at":"2024-07-30T20:00:51.555Z","updated_at":"2025-05-15T08:05:05.937Z","avatar_url":"https://github.com/benedekrozemberczki.png","language":"Python","funding_links":["https://github.com/sponsors/benedekrozemberczki"],"categories":["Uncategorized","Other Awesome Lists","Technical","Python","Others","To Sort","Table of Contents","Other","Books","梯度提升和树模型","Other Lists","Awesome lists","Awesome List","Related Awesome Lists","Learning","📦 Miscellaneous","ML Sub-fields","Core Machine Learning Research"],"sub_categories":["Uncategorized","Comics","awesome-*","Data Visualization","Free Courses","TeX Lists","Awesome papers","Ukraine","Comparison Studies","🏆 Top 25","General ML, Surveys, and Methods"],"readme":"# Awesome Decision, Classification, and Regression Tree Research Papers\n[![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome)\n[![PRs Welcome](https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square)](http://makeapullrequest.com)\n[![repo size](https://img.shields.io/github/repo-size/benedekrozemberczki/awesome-decision-tree-papers.svg)](https://github.com/benedekrozemberczki/awesome-decision-tree-papers/archive/master.zip)\n ![License](https://img.shields.io/github/license/benedekrozemberczki/awesome-decision-tree-papers.svg?color=blue) [![benedekrozemberczki](https://img.shields.io/twitter/follow/benrozemberczki?style=social\u0026logo=twitter)](https://twitter.com/intent/follow?screen_name=benrozemberczki)\n\u003cp align=\"center\"\u003e\n  \u003cimg width=\"300\" src=\"tree.png\"\u003e\n\u003c/p\u003e\n\nA curated list of classification and regression tree research papers with implementations from the following conferences:\n\n- Machine learning\n   * [NeurIPS](https://nips.cc/) \n   * [ICML](https://icml.cc/) \n   * [ICLR](https://iclr.cc/)\n- Computer vision\n   * [CVPR](http://cvpr2019.thecvf.com/)\n   * [ICCV](http://iccv2019.thecvf.com/)\n   * [ECCV](https://eccv2018.org/)\n- Natural language processing\n   * [ACL](http://www.acl2019.org/EN/index.xhtml)\n   * [NAACL](https://naacl2019.org/)\n   * [EMNLP](https://www.emnlp-ijcnlp2019.org/) \n- Data\n   * [KDD](https://www.kdd.org/)\n   * [CIKM](http://www.cikmconference.org/)   \n   * [ICDM](http://icdm2019.bigke.org/)\n   * [SDM](https://www.siam.org/Conferences/CM/Conference/sdm19)   \n   * [PAKDD](http://pakdd2019.medmeeting.org)\n   * [PKDD/ECML](http://ecmlpkdd2019.org)\n   * [SIGIR](https://sigir.org/)\n   * [WWW](https://www2019.thewebconf.org/)\n   * [WSDM](www.wsdm-conference.org) \n- Artificial intelligence\n   * [AAAI](https://www.aaai.org/)\n   * [AISTATS](https://www.aistats.org/)\n   * [ICANN](https://e-nns.org/icann2019/)   \n   * [IJCAI](https://www.ijcai.org/)\n   * [UAI](http://www.auai.org/)\n\nSimilar collections about [graph classification](https://github.com/benedekrozemberczki/awesome-graph-classification), [gradient boosting](https://github.com/benedekrozemberczki/awesome-gradient-boosting-papers), [fraud detection](https://github.com/benedekrozemberczki/awesome-fraud-detection-papers), [Monte Carlo tree search](https://github.com/benedekrozemberczki/awesome-monte-carlo-tree-search-papers), and [community detection](https://github.com/benedekrozemberczki/awesome-community-detection) papers with implementations.\n\n## 2022\n\n- **Using MaxSAT for Efficient Explanations of Tree Ensembles (AAAI 2022)**\n  - Alexey Ignatiev, Yacine Izza, Peter J. Stuckey, João Marques-Silva\n  - [[Paper]](https://alexeyignatiev.github.io/assets/pdf/iisms-aaai22-preprint.pdf)\n\n- **FOCUS: Flexible Optimizable Counterfactual Explanations for Tree Ensembles (AAAI 2022)**\n  - Ana Lucic, Harrie Oosterhuis, Hinda Haned, Maarten de Rijke\n  - [[Paper]](https://a-lucic.github.io/talks/ICML_SMRL_focus.pdf)\n\n- **Explainable and Local Correction of Classification Models Using Decision Trees (AAAI 2022)**\n  - Hirofumi Suzuki, Hiroaki Iwashita, Takuya Takagi, Keisuke Goto, Yuta Fujishige, Satoshi Hara\n  - [[Paper]](https://ojs.aaai.org/index.php/AAAI/article/view/20816)\n\n- **Robust Optimal Classification Trees against Adversarial Examples (AAAI 2022)**\n  - Daniël Vos, Sicco Verwer\n  - [[Paper]](https://arxiv.org/abs/2109.03857)\n\n- **Fairness without Imputation: A Decision Tree Approach for Fair Prediction with Missing Values (AAAI 2022)**\n  - Haewon Jeong, Hao Wang, Flávio P. Calmon\n  - [[Paper]](https://arxiv.org/abs/2109.10431)\n\n- **Fast Sparse Decision Tree Optimization via Reference Ensembles (AAAI 2022)**\n  - Hayden McTavish, Chudi Zhong, Reto Achermann, Ilias Karimalis, Jacques Chen, Cynthia Rudin, Margo I. Seltzer\n  - [[Paper]](https://arxiv.org/abs/2112.00798)\n  - [[Code]](https://pypi.org/project/gosdt/)\n\n- **TransBoost: A Boosting-Tree Kernel Transfer Learning Algorithm for Improving Financial Inclusion (AAAI 2022)**\n  - Yiheng Sun, Tian Lu, Cong Wang, Yuan Li, Huaiyu Fu, Jingran Dong, Yunjie Xu\n  - [[Paper]](https://arxiv.org/abs/2112.02365)\n  - [[Code]](https://github.com/yihengsun/TransBoost)\n\n- **Counterfactual Explanation Trees: Transparent and Consistent Actionable Recourse with Decision Trees (AISTATS 2022)**\n  - Kentaro Kanamori, Takuya Takagi, Ken Kobayashi, Yuichi Ike\n  - [[Paper]](https://proceedings.mlr.press/v151/kanamori22a.html)\n\n- **Accurate Shapley Values for explaining tree-based models (AISTATS 2022)**\n  - Salim I. Amoukou, Tangi Salaün, Nicolas J.-B. Brunel\n  - [[Paper]](https://arxiv.org/abs/2106.03820)\n\n- **A cautionary tale on fitting decision trees to data from additive models: generalization lower bounds (AISTATS 2022)**\n  - Yan Shuo Tan, Abhineet Agarwal, Bin Yu\n  - [[Paper]](https://arxiv.org/abs/2110.09626)\n  - [[Code]](https://github.com/aagarwal1996/additive_trees)\n\n- **Enterprise-Scale Search: Accelerating Inference for Sparse Extreme Multi-Label Ranking Trees (WWW 2022)**\n  - Philip A. Etter, Kai Zhong, Hsiang-Fu Yu, Lexing Ying, Inderjit S. Dhillon\n  - [[Paper]](https://arxiv.org/abs/2106.02697)\n\n- **MBCT: Tree-Based Feature-Aware Binning for Individual Uncertainty Calibration (WWW 2022)**\n  - Siguang Huang, Yunli Wang, Lili Mou, Huayue Zhang, Han Zhu, Chuan Yu, Bo Zheng\n  - [[Paper]](https://arxiv.org/abs/2202.04348)\n\n- **Rethinking Conversational Recommendations: Is Decision Tree All You Need (CIKM 2022)**\n  - A S. M. Ahsan-Ul-Haque, Hongning Wang\n  - [[Paper]](https://arxiv.org/abs/2208.14614)\n\n- **A Neural Tangent Kernel Perspective of Infinite Tree Ensembles (ICLR 2022)**\n  - Ryuichi Kanoh, Mahito Sugiyama\n  - [[Paper]](https://openreview.net/forum?id=vUH85MOXO7h)\n \n- **POETREE: Interpretable Policy Learning with Adaptive Decision Trees (ICLR 2022)**\n  - Alizée Pace, Alex Chan, Mihaela van der Schaar\n  - [[Paper]](https://arxiv.org/abs/2203.08057)\n\n- **Hierarchical Shrinkage: Improving the accuracy and interpretability of tree-based models (ICML 2022)**\n  - Abhineet Agarwal, Yan Shuo Tan, Omer Ronen, Chandan Singh, Bin Yu\n  - [[Paper]](https://arxiv.org/abs/2202.00858)\n\n- **Popular decision tree algorithms are provably noise tolerant (ICML 2022)**\n  - Guy Blanc, Jane Lange, Ali Malik, Li-Yang Tan\n  - [[Paper]](https://arxiv.org/abs/2206.08899)\n\n- **Robust Counterfactual Explanations for Tree-Based Ensembles (ICML 2022)**\n  - Sanghamitra Dutta, Jason Long, Saumitra Mishra, Cecilia Tilli, Daniele Magazzeni\n  - [[Paper]](https://proceedings.mlr.press/v162/dutta22a.html)\n\n- **Fast Provably Robust Decision Trees and Boosting (ICML 2022)**\n  - Jun-Qi Guo, Ming-Zhuo Teng, Wei Gao, Zhi-Hua Zhou\n  - [[Paper]](https://proceedings.mlr.press/v162/guo22h.html)\n\n- **BAMDT: Bayesian Additive Semi-Multivariate Decision Trees for Nonparametric Regression (ICML 2022)**\n  - Zhao Tang Luo, Huiyan Sang, Bani K. Mallick\n  - [[Paper]](https://proceedings.mlr.press/v162/luo22a.html)\n\n- **Quant-BnB: A Scalable Branch-and-Bound Method for Optimal Decision Trees with Continuous Features (ICML 2022)**\n  - Rahul Mazumder, Xiang Meng, Haoyue Wang\n  - [[Paper]](https://arxiv.org/abs/2206.11844)\n\n- **A Tree-based Model Averaging Approach for Personalized Treatment Effect Estimation from Heterogeneous Data Sources (ICML 2022)**\n  - Xiaoqing Tan, Chung-Chou H. Chang, Ling Zhou, Lu Tang\n  - [[Paper]](https://arxiv.org/abs/2103.06261)\n\n- **On Preferred Abductive Explanations for Decision Trees and Random Forests (IJCAI 2022)**\n  - Gilles Audemard, Steve Bellart, Louenas Bounia, Frédéric Koriche, Jean-Marie Lagniez, Pierre Marquis\n  - [[Paper]](https://www.ijcai.org/proceedings/2022/0091.pdf)\n\n- **Extending Decision Tree to Handle Multiple Fairness Criteria (IJCAI 2022)**\n  - Alessandro Castelnovo\n  - [[Paper]](https://www.ijcai.org/proceedings/2022/0822.pdf)\n\n- **Flexible Modeling and Multitask Learning using Differentiable Tree Ensembles (KDD 2022)**\n  - Shibal Ibrahim, Hussein Hazimeh, Rahul Mazumder\n  - [[Paper]](https://arxiv.org/abs/2205.09717)\n\n- **Integrity Authentication in Tree Models (KDD 2022)**\n  - Weijie Zhao, Yingjie Lao, Ping Li\n  - [[Paper]](https://dl.acm.org/doi/abs/10.1145/3534678.3539428)\n\n- **Retrieval-Based Gradient Boosting Decision Trees for Disease Risk Assessment (KDD 2022)**\n  - Handong Ma, Jiahang Cao, Yuchen Fang, Weinan Zhang, Wenbo Sheng, Shaodian Zhang, Yong Yu\n  - [[Paper]](https://dl.acm.org/doi/abs/10.1145/3534678.3539052)\n\n- **Improved feature importance computation for tree models based on the Banzhaf value (UAI 2022)**\n  - Adam Karczmarz, Tomasz Michalak, Anish Mukherjee, Piotr Sankowski, Piotr Wygocki\n  - [[Paper]](https://proceedings.mlr.press/v180/karczmarz22a.html)\n\n- **Learning linear non-Gaussian polytree models (UAI 2022)**\n  - Daniele Tramontano, Anthea Monod, Mathias Drton\n  - [[Paper]](https://arxiv.org/abs/2208.06701)\n\n## 2021\n\n- **Online Probabilistic Label Trees (AISTATS 2021)**\n  - Kalina Jasinska-Kobus, Marek Wydmuch, Devanathan Thiruvenkatachari, Krzysztof Dembczyński\n  - [[Paper]](https://arxiv.org/abs/2007.04451)\n  - [[Code]](https://github.com/mwydmuch/napkinXC)\n\n- **Optimal Decision Trees for Nonlinear Metrics (AAAI 2021)**\n  - Emir Demirovic, Peter J. Stuckey\n  - [[Paper]](https://arxiv.org/abs/2009.06921)\n\n- **SAT-based Decision Tree Learning for Large Data Sets (AAAI 2021)**\n  - André Schidler, Stefan Szeider\n  - [[Paper]](https://ojs.aaai.org/index.php/AAAI/article/view/16509)\n\n- **Parameterized Complexity of Small Decision Tree Learning (AAAI 2021)**\n  - Sebastian Ordyniak, Stefan Szeider\n  - [[Paper]](https://www.ac.tuwien.ac.at/files/tr/ac-tr-21-002.pdf)\n\n- **Counterfactual Explanations for Oblique Decision Trees: Exact - Efficient Algorithms (AAAI 2021)**\n  - Miguel Á. Carreira-Perpiñán, Suryabhan Singh Hada\n  - [[Paper]](https://arxiv.org/abs/2103.01096)\n\n- **Geometric Heuristics for Transfer Learning in Decision Trees (CIKM 2021)**\n  - Siddhesh Chaubal, Mateusz Rzepecki, Patrick K. Nicholson, Guangyuan Piao, Alessandra Sala\n  - [[Paper]](https://dl.acm.org/doi/abs/10.1145/3459637.3482259)\n\n- **Fairness-Aware Training of Decision Trees by Abstract Interpretation (CIKM 2021)**\n  - Francesco Ranzato, Caterina Urban, Marco Zanella\n  - [[Paper]](https://dl.acm.org/doi/abs/10.1145/3459637.3482342)\n\n- **Enabling Efficiency-Precision Trade-offs for Label Trees in Extreme Classification (CIKM 2021)**\n  - Tavor Z. Baharav, Daniel L. Jiang, Kedarnath Kolluri, Sujay Sanghavi, Inderjit S. Dhillon\n  - [[Paper]](https://arxiv.org/abs/2106.00730)\n\n- **Are Neural Rankers still Outperformed by Gradient Boosted Decision Trees (ICLR 2021)**\n  - Zhen Qin, Le Yan, Honglei Zhuang, Yi Tay, Rama Kumar Pasumarthi, Xuanhui Wang, Michael Bendersky, Marc Najork\n  - [[Paper]](https://openreview.net/forum?id=Ut1vF_q_vC)\n\n- **NBDT: Neural-Backed Decision Tree (ICLR 2021)**\n  - Alvin Wan, Lisa Dunlap, Daniel Ho, Jihan Yin, Scott Lee, Suzanne Petryk, Sarah Adel Bargal, Joseph E. Gonzalez\n  - [[Paper]](https://arxiv.org/abs/2004.00221)\n\n- **Versatile Verification of Tree Ensembles (ICML 2021)**\n  - Laurens Devos, Wannes Meert, Jesse Davis\n  - [[Paper]](https://arxiv.org/abs/2010.13880)\n\n- **Connecting Interpretability and Robustness in Decision Trees through Separation (ICML 2021)**\n  - Michal Moshkovitz, Yao-Yuan Yang, Kamalika Chaudhuri\n  - [[Paper]](https://arxiv.org/abs/2102.07048)\n\n- **Optimal Counterfactual Explanations in Tree Ensembles (ICML 2021)**\n  - Axel Parmentier, Thibaut Vidal\n  - [[Paper]](https://arxiv.org/abs/2106.06631)\n\n- **Efficient Training of Robust Decision Trees Against Adversarial Examples (ICML 2021)**\n  - Daniël Vos, Sicco Verwer\n  - [[Paper]](https://arxiv.org/abs/2012.10438)\n\n- **Learning Binary Decision Trees by Argmin Differentiation (ICML 2021)**\n  - Valentina Zantedeschi, Matt J. Kusner, Vlad Niculae\n  - [[Paper]](https://arxiv.org/pdf/2010.04627.pdf)\n \n- **BLOCKSET (Block-Aligned Serialized Trees): Reducing Inference Latency for Tree ensemble Deployment (KDD 2021)**\n  - Meghana Madhyastha, Kunal Lillaney, James Browne, Joshua T. Vogelstein, Randal Burns\n  - [[Paper]](https://dl.acm.org/doi/abs/10.1145/3447548.3467368)\n\n- **ControlBurn: Feature Selection by Sparse Forests (KDD 2021)**\n  - Brian Liu, Miaolan Xie, Madeleine Udell\n  - [[Paper]](https://dl.acm.org/doi/abs/10.1145/3447548.3467387?sid=SCITRUS)\n\n- **Probabilistic Gradient Boosting Machines for Large-Scale Probabilistic Regression (KDD 2021)**\n  - Olivier Sprangers, Sebastian Schelter, Maarten de Rijke\n  - [[Paper]](https://dl.acm.org/doi/10.1145/3447548.3467278)\n\n- **Verifying Tree Ensembles by Reasoning about Potential Instances (SDM 2021)**\n  - Laurens Devos, Wannes Meert, Jesse Davis\n  - [[Paper]](https://arxiv.org/abs/2001.11905)\n\n## 2020\n\n- **DTCA: Decision Tree-based Co-Attention Networks for Explainable Claim Verification (ACL 2020)**\n  - Lianwei Wu, Yuan Rao, Yongqiang Zhao, Hao Liang, Ambreen Nazir\n  - [[Paper]](https://arxiv.org/abs/2004.13455)\n\n- **Privacy-Preserving Gradient Boosting Decision Trees (AAAI 2020)**\n  - Qinbin Li, Zhaomin Wu, Zeyi Wen, Bingsheng He\n  - [[Paper]](https://arxiv.org/abs/1911.04209)\n\n- **Practical Federated Gradient Boosting Decision Trees (AAAI 2020)**\n  - Qinbin Li, Zeyi Wen, Bingsheng He\n  - [[Paper]](https://arxiv.org/abs/1911.04206)\n\n- **Efficient Inference of Optimal Decision Trees (AAAI 2020)**\n  - Florent Avellaneda\n  - [[Paper]](http://florent.avellaneda.free.fr/dl/AAAI20.pdf)\n  - [[Code]](https://github.com/FlorentAvellaneda/InferDT)\n\n- **Learning Optimal Decision Trees Using Caching Branch-and-Bound Search (AAAI 2020)**\n  - Gael Aglin, Siegfried Nijssen, Pierre Schaus\n  - [[Paper]](https://dial.uclouvain.be/pr/boreal/fr/object/boreal%3A223390/datastream/PDF_01/view)\n  - [[Code]](https://pypi.org/project/dl8.5/)\n\n- **Abstract Interpretation of Decision Tree Ensemble Classifiers (AAAI 2020)**\n  - Francesco Ranzato, Marco Zanella\n  - [[Paper]](https://www.math.unipd.it/~ranzato/papers/aaai20.pdf)\n  - [[Code]](https://github.com/abstract-machine-learning/silva)\n\n- **Scalable Feature Selection for (Multitask) Gradient Boosted Trees (AISTATS 2020)**\n  - Cuize Han, Nikhil Rao, Daria Sorokina, Karthik Subbian\n  - [[Paper]](http://proceedings.mlr.press/v108/han20a.html)\n\n- **Optimization Methods for Interpretable Differentiable Decision Trees Applied to Reinforcement Learning (AISTATS 2020)**\n  - Andrew Silva, Matthew C. Gombolay, Taylor W. Killian, Ivan Dario Jimenez Jimenez, Sung-Hyun Son\n  - [[Paper]](https://arxiv.org/abs/1903.09338)\n\n- **Exploiting Categorical Structure Using Tree-Based Methods (AISTATS 2020)**\n  - Brian Lucena\n  - [[Paper]](https://arxiv.org/abs/2004.07383)\n\n- **LdSM: Logarithm-depth Streaming Multi-label Decision Trees (AISTATS 2020)**\n  - Maryam Majzoubi, Anna Choromanska\n  - [[Paper]](https://arxiv.org/abs/1905.10428)\n  \n- **Oblique Decision Trees from Derivatives of ReLU Networks (ICLR 2020)**\n  - Guang-He Lee, Tommi S. Jaakkola\n  - [[Paper]](https://openreview.net/pdf?id=Bke8UR4FPB)\n  - [[Code]](https://github.com/guanghelee/iclr20-lcn)\n  \n- **Provable Guarantees for Decision Tree Induction: the Agnostic Setting (ICML 2020)**\n  - Guy Blanc, Jane Lange, Li-Yang Tan\n  - [[Paper]](https://arxiv.org/abs/2006.00743v1)\n\n- **Decision Trees for Decision-Making under the Predict-then-Optimize Framework (ICML 2020)**\n  - Adam N. Elmachtoub, Jason Cheuk Nam Liang, Ryan McNellis\n  - [[Paper]](https://arxiv.org/abs/2003.00360)\n\n- **The Tree Ensemble Layer: Differentiability meets Conditional Computation (ICML 2020)**\n  - Hussein Hazimeh, Natalia Ponomareva, Petros Mol, Zhenyu Tan, Rahul Mazumder\n  - [[Paper]](https://arxiv.org/abs/2002.07772)\n  - [[Code]](https://github.com/google-research/google-research/tree/master/tf_trees)\n\n- **Generalized and Scalable Optimal Sparse Decision Trees (ICML 2020)**\n  - Jimmy Lin, Chudi Zhong, Diane Hu, Cynthia Rudin, Margo I. Seltzer\n  - [[Paper]](https://arxiv.org/abs/2006.08690)\n  - [[Code]](https://github.com/xiyanghu/OSDT)\n\n- **Born-Again Tree Ensembles (ICML 2020)**\n  - Thibaut Vidal, Maximilian Schiffer\n  - [[Paper]](https://arxiv.org/abs/2003.11132)\n  - [[Code]](https://github.com/vidalt/BA-Trees)\n\n- **On Lp-norm Robustness of Ensemble Decision Stumps and Trees (ICML 2020)**\n  - Yihan Wang, Huan Zhang, Hongge Chen, Duane S. Boning, Cho-Jui Hsieh\n  - [[Paper]](https://arxiv.org/abs/2008.08755)\n\n- **Smaller, More Accurate Regression Forests Using Tree Alternating Optimization (ICML 2020)**\n  - Arman Zharmagambetov, Miguel Á. Carreira-Perpinan\n  - [[Paper]](http://proceedings.mlr.press/v119/zharmagambetov20a.html)\n  \n- **Learning Optimal Decision Trees with MaxSAT and its Integration in AdaBoost (IJCAI 2020)**\n  - Hao Hu, Mohamed Siala, Emmanuel Hebrard, Marie-José Huguet\n  - [[Paper]](https://www.ijcai.org/Proceedings/2020/163)\n\n- **Speeding up Very Fast Decision Tree with Low Computational Cost (IJCAI 2020)**\n  - Jian Sun, Hongyu Jia, Bo Hu, Xiao Huang, Hao Zhang, Hai Wan, Xibin Zhao\n  - [[Paper]](https://www.ijcai.org/Proceedings/2020/0177.pdf)\n\n- **PyDL8.5: a Library for Learning Optimal Decision Trees (IJCAI 2020)**\n  - Gaël Aglin, Siegfried Nijssen, Pierre Schaus\n  - [[Paper]](https://www.ijcai.org/Proceedings/2020/0750.pdf)\n  - [[Code]](https://github.com/aia-uclouvain/pydl8.5)\n\n- **Geodesic Forests (KDD 2020)**\n  - Meghana Madhyastha, Gongkai Li, Veronika Strnadova-Neeley, James Browne, Joshua T. Vogelstein, Randal Burns\n  - [[Paper]](https://dl.acm.org/doi/pdf/10.1145/3394486.3403094)\n\n- **A Scalable MIP-based Method for Learning Optimal Multivariate Decision Trees (NeurIPS 2020)**\n  - Haoran Zhu, Pavankumar Murali, Dzung T. Phan, Lam M. Nguyen, Jayant Kalagnanam\n  - [[Paper]](https://arxiv.org/abs/2011.03375)\n\n- **Estimating Decision Tree Learnability with Polylogarithmic Sample Complexity (NeurIPS 2020)**\n  - Guy Blanc, Neha Gupta, Jane Lange, Li-Yang Tan\n  - [[Paper]](https://arxiv.org/abs/2011.01584)\n \n- **Universal Guarantees for Decision Tree Induction via a Higher-Order Splitting Criterion (NeurIPS 2020)**\n  - Guy Blanc, Neha Gupta, Jane Lange, Li-Yang Tan\n  - [[Paper]](https://arxiv.org/abs/2010.08633)\n\n- **Smooth And Consistent Probabilistic Regression Trees (NeurIPS 2020)**\n  - Sami Alkhoury, Emilie Devijver, Marianne Clausel, Myriam Tami, Éric Gaussier, Georges Oppenheim\n  - [[Paper]](https://papers.nips.cc/paper/2020/file/8289889263db4a40463e3f358bb7c7a1-Paper.pdf)\n\n- **An Efficient Adversarial Attack for Tree Ensembles (NeurIPS 2020)**\n  - Chong Zhang, Huan Zhang, Cho-Jui Hsieh\n  - [[Paper]](https://arxiv.org/abs/2010.11598)\n  - [[Code]](https://github.com/chong-z/tree-ensemble-attack)\n\n- **Decision Trees as Partitioning Machines to Characterize their Generalization Properties (NeurIPS 2020)**\n  - Jean-Samuel Leboeuf, Frédéric Leblanc, Mario Marchand\n  - [[Paper]](https://papers.nips.cc/paper/2020/file/d2a10b0bd670e442b1d3caa3fbf9e695-Paper.pdf)\n  \n- **Evidence Weighted Tree Ensembles for Text Classification (SIGIR 2020)**\n  - Md. Zahidul Islam, Jixue Liu, Jiuyong Li, Lin Liu, Wei Kang\n  - [[Paper]](https://dl.acm.org/doi/abs/10.1145/3397271.3401229)\n  \n## 2019\n\n- **Multi Level Deep Cascade Trees for Conversion Rate Prediction in Recommendation System (AAAI 2019)**\n  - Hong Wen, Jing Zhang, Quan Lin, Keping Yang, Pipei Huang\n  - [[Paper]](https://arxiv.org/pdf/1805.09484.pdf)\n  \n- **Induction of Non-Monotonic Logic Programs to Explain Boosted Tree Models Using LIME (AAAI 2019)**\n  - Farhad Shakerin, Gopal Gupta\n  - [[Paper]](https://arxiv.org/abs/1808.00629)\n  \n- **Learning Optimal and Fair Decision Trees for Non-Discriminative Decision-Making (AAAI 2019)**\n  - Sina Aghaei, Mohammad Javad Azizi, Phebe Vayanos\n  - [[Paper]](https://arxiv.org/abs/1903.10598)\n\n- **Desiderata for Interpretability: Explaining Decision Tree Predictions with Counterfactuals (AAAI 2019)**\n  - Kacper Sokol, Peter A. Flach\n  - [[Paper]](https://aaai.org/ojs/index.php/AAAI/article/view/5154)\n  \n- **Weighted Oblique Decision Trees (AAAI 2019)**\n  - Bin-Bin Yang, Song-Qing Shen, Wei Gao\n  - [[Paper]](https://aaai.org/ojs/index.php/AAAI/article/view/4505)\n\n- **Learning Optimal Classification Trees Using a Binary Linear Program Formulation (AAAI 2019)**\n  - Sicco Verwer, Yingqian Zhang\n  - [[Paper]](https://yingqianzhang.net/wp-content/uploads/2018/12/VerwerZhangAAAI-final.pdf)\n\n- **Optimization of Hierarchical Regression Model with Application to Optimizing Multi-Response Regression K-ary Trees (AAAI 2019)**\n  - Pooya Tavallali, Peyman Tavallali, Mukesh Singhal\n  - [[Paper]](https://aaai.org/ojs/index.php/AAAI/article/view/4447/4325)\n\n- **XBART: Accelerated Bayesian Additive Regression Trees (AISTATS 2019)**\n  - Jingyu He, Saar Yalov, P. Richard Hahn\n  - [[Paper]](https://arxiv.org/abs/1810.02215)\n\n- **Interaction Detection with Bayesian Decision Tree Ensembles (AISTATS 2019)**\n  - Junliang Du, Antonio R. Linero\n  - [[Paper]](https://arxiv.org/abs/1809.08524)\n  \n- **Adversarial Training of Gradient-Boosted Decision Trees (CIKM 2019)**\n  - Stefano Calzavara, Claudio Lucchese, Gabriele Tolomei\n  - [[Paper]](https://www.dais.unive.it/~calzavara/papers/cikm19.pdf)\n\n- **Interpretable MTL from Heterogeneous Domains using Boosted Tree (CIKM 2019)**\n  - Ya-Lin Zhang, Longfei Li\n  - [[Paper]](https://dl.acm.org/citation.cfm?id=3357384.3358072)\n\n- **Interpreting CNNs via Decision Trees (CVPR 2019)**\n  - Quanshi Zhang, Yu Yang, Haotian Ma, Ying Nian Wu\n  - [[Paper]](https://arxiv.org/abs/1802.00121)\n  \n- **EDiT: Interpreting Ensemble Models via Compact Soft Decision Trees (ICDM 2019)**\n  - Jaemin Yoo, Lee Sael\n  - [[Paper]](https://github.com/leesael/EDiT/blob/master/docs/YooS19.pdf)\n  - [[Code]](https://github.com/leesael/EDiT)\n\n- **Fair Adversarial Gradient Tree Boosting (ICDM 2019)**\n  - Vincent Grari, Boris Ruf, Sylvain Lamprier, Marcin Detyniecki\n  - [[Paper]](https://arxiv.org/abs/1911.05369)\n\n- **Functional Transparency for Structured Data: a Game-Theoretic Approach (ICML 2019)**\n  - Guang-He Lee, Wengong Jin, David Alvarez-Melis, Tommi S. Jaakkola\n  - [[Paper]](http://proceedings.mlr.press/v97/lee19b/lee19b.pdf)\n  \n- **Incorporating Grouping Information into Bayesian Decision Tree Ensembles (ICML 2019)**\n  - Junliang Du, Antonio R. Linero\n  - [[Paper]](http://proceedings.mlr.press/v97/du19d.html)\n\n- **Adaptive Neural Trees (ICML 2019)**\n  - Ryutaro Tanno, Kai Arulkumaran, Daniel C. Alexander, Antonio Criminisi, Aditya V. Nori\n  - [[Paper]](https://arxiv.org/abs/1807.06699)\n  - [[Code]](https://github.com/rtanno21609/AdaptiveNeuralTrees)\n\n- **Robust Decision Trees Against Adversarial Examples (ICML 2019)**\n  - Hongge Chen, Huan Zhang, Duane S. Boning, Cho-Jui Hsieh\n  - [[Paper]](https://arxiv.org/abs/1902.10660)\n  - [[Code]](https://github.com/chenhongge/RobustTrees)\n  \n- **Learn Smart with Less: Building Better Online Decision Trees with Fewer Training Examples (IJCAI 2019)**\n  - Ariyam Das, Jin Wang, Sahil M. Gandhi, Jae Lee, Wei Wang, Carlo Zaniolo\n  - [[Paper]](https://www.ijcai.org/proceedings/2019/0306.pdf)\n  \n- **FAHT: An Adaptive Fairness-aware Decision Tree Classifier (IJCAI 2019)**\n  - Wenbin Zhang, Eirini Ntoutsi\n  - [[Paper]](https://arxiv.org/abs/1907.07237)\n  - [[Code]](https://github.com/vanbanTruong/FAHT)\n\n- **Inter-node Hellinger Distance based Decision Tree (IJCAI 2019)**\n  - Pritom Saha Akash, Md. Eusha Kadir, Amin Ahsan Ali, Mohammad Shoyaib\n  - [[Paper]](https://www.ijcai.org/proceedings/2019/0272.pdf)\n  - [[Matlab Code]](https://github.com/ZDanielsResearch/HellingerTreesMatlab)\n  - [[R Code]](https://github.com/kaustubhrpatil/HDDT)\n\n- **Gradient Boosting with Piece-Wise Linear Regression Trees (IJCAI 2019)**\n  - Yu Shi, Jian Li, Zhize Li\n  - [[Paper]](https://arxiv.org/abs/1802.05640)\n  - [[Code]](https://github.com/GBDT-PL/GBDT-PL)\n\n- **A Gradient-Based Split Criterion for Highly Accurate and Transparent Model Trees (IJCAI 2019)**\n  - Klaus Broelemann, Gjergji Kasneci\n  - [[Paper]](https://arxiv.org/abs/1809.09703)\n  \n- **Combining Decision Trees and Neural Networks for Learning-to-Rank in Personal Search (KDD 2019)**\n  - Pan Li, Zhen Qin, Xuanhui Wang, Donald Metzler\n  - [[Paper]](https://ai.google/research/pubs/pub48133/)\n  \n- **Tight Certificates of Adversarial Robustness for Randomly Smoothed Classifiers (NeurIPS 2019)**\n  - Guang-He Lee, Yang Yuan, Shiyu Chang, Tommi S. Jaakkola\n  - [[Paper]](https://papers.nips.cc/paper/8737-tight-certificates-of-adversarial-robustness-for-randomly-smoothed-classifiers.pdf)\n  - [[Code]](https://github.com/guanghelee/Randomized_Smoothing)\n\n- **Partitioning Structure Learning for Segmented Linear Regression Trees (NeurIPS 2019)**\n  - Xiangyu Zheng, Song Xi Chen\n  - [[Paper]](https://papers.nips.cc/paper/8494-partitioning-structure-learning-for-segmented-linear-regression-trees)\n  \n- **Provably Robust Boosted Decision Stumps and Trees against Adversarial Attacks (NeurIPS 2019)**\n  - Maksym Andriushchenko, Matthias Hein\n  - [[Paper]](https://arxiv.org/abs/1906.03526)\n  - [[Code]](https://github.com/max-andr/provably-robust-boosting)\n\n- **Optimal Decision Tree with Noisy Outcomes (NeurIPS 2019)**\n  - Su Jia, Viswanath Nagarajan, Fatemeh Navidi, R. Ravi\n  - [[Paper]](https://papers.nips.cc/paper/8592-optimal-decision-tree-with-noisy-outcomes.pdf)\n  - [[Code]](https://github.com/sjia1/ODT-with-noisy-outcomes)\n\n- **Regularized Gradient Boosting (NeurIPS 2019)**\n  - Corinna Cortes, Mehryar Mohri, Dmitry Storcheus\n  - [[Paper]](https://papers.nips.cc/paper/8784-regularized-gradient-boosting.pdf)\n\n- **Optimal Sparse Decision Trees (NeurIPS 2019)**\n  - Xiyang Hu, Cynthia Rudin, Margo Seltzer\n  - [[Paper]](https://papers.nips.cc/paper/8947-optimal-sparse-decision-trees.pdf)\n  - [[Code]](https://github.com/xiyanghu/OSDT)\n  \n- **MonoForest framework for tree ensemble analysis (NeurIPS 2019)**\n  - Igor Kuralenok, Vasilii Ershov, Igor Labutin\n  - [[Paper]](https://papers.nips.cc/paper/9530-monoforest-framework-for-tree-ensemble-analysis)\n  - [[Code]](https://github.com/xiyanghu/OSDT)\n\n- **Calibrating Probability Estimation Trees using Venn-Abers Predictors (SDM 2019)**\n  - Ulf Johansson, Tuwe Löfström, Henrik Boström\n  - [[Paper]](https://epubs.siam.org/doi/pdf/10.1137/1.9781611975673.4)\n  \n- **Fast Training for Large-Scale One-versus-All Linear Classifiers using Tree-Structured Initialization (SDM 2019)**\n  - Huang Fang, Minhao Cheng, Cho-Jui Hsieh, Michael P. Friedlander\n  - [[Paper]](https://epubs.siam.org/doi/pdf/10.1137/1.9781611975673.32)\n\n- **Forest Packing: Fast Parallel, Decision Forests (SDM 2019)**\n  - James Browne, Disa Mhembere, Tyler M. Tomita, Joshua T. Vogelstein, Randal Burns\n  - [[Paper]](https://epubs.siam.org/doi/abs/10.1137/1.9781611975673.6)\n  \n- **Block-distributed Gradient Boosted Trees (SIGIR 2019)**\n  - Theodore Vasiloudis, Hyunsu Cho, Henrik Boström\n  - [[Paper]](https://arxiv.org/abs/1904.10522)\n  \n- **Entity Personalized Talent Search Models with Tree Interaction Features (WWW 2019)**\n  - Cagri Ozcaglar, Sahin Cem Geyik, Brian Schmitz, Prakhar Sharma, Alex Shelkovnykov, Yiming Ma, Erik Buchanan\n  - [[Paper]](https://arxiv.org/abs/1902.09041)\n\n## 2018\n- **Adapting to Concept Drift in Credit Card Transaction Data Streams Using Contextual Bandits and Decision Trees (AAAI 2018)**\n  - Dennis J. N. J. Soemers, Tim Brys, Kurt Driessens, Mark H. M. Winands, Ann Nowé\n  - [[Paper]](https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/viewFile/16183/16394)\n\n- **MERCS: Multi-Directional Ensembles of Regression and Classification Trees (AAAI 2018)**\n  - Elia Van Wolputte, Evgeniya Korneva, Hendrik Blockeel\n  - [[Paper]](https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/viewFile/16875/16735)\n  - [[Code]](https://github.com/eliavw/mercs-v5)\n\n- **Differential Performance Debugging With Discriminant Regression Trees (AAAI 2018)**\n  - Saeid Tizpaz-Niari, Pavol Cerný, Bor-Yuh Evan Chang, Ashutosh Trivedi\n  - [[Paper]](https://arxiv.org/abs/1711.04076)\n  - [[Code]](https://github.com/cuplv/DPDEBUGGER)\n\n- **Estimating the Class Prior in Positive and Unlabeled Data Through Decision Tree Induction (AAAI 2018)**\n  - Jessa Bekker, Jesse Davis\n  - [[Paper]](https://aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/16776)\n\n- **MDP-Based Cost Sensitive Classification Using Decision Trees (AAAI 2018)**\n  - Shlomi Maliah, Guy Shani\n  - [[Paper]](https://aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/17128)\n\n- **Generative Adversarial Image Synthesis With Decision Tree Latent Controller (CVPR 2018)**\n  - Takuhiro Kaneko, Kaoru Hiramatsu, Kunio Kashino\n  - [[Paper]](https://arxiv.org/abs/1805.10603)\n  - [[Code]](https://github.com/LynnHo/DTLC-GAN-Tensorflow)\n\n- **Enhancing Very Fast Decision Trees with Local Split-Time Predictions (ICDM 2018)**\n  - Viktor Losing, Heiko Wersing, Barbara Hammer\n  - [[Paper]](https://www.techfak.uni-bielefeld.de/~hwersing/LosingHammerWersing_ICDM2018.pdf)\n  - [[Code]](https://github.com/ICDM2018Submission/VFDT-split-time-prediction)\n  \n- **Realization of Random Forest for Real-Time Evaluation through Tree Framing (ICDM 2018)**\n  - Sebastian Buschjäger, Kuan-Hsun Chen, Jian-Jia Chen, Katharina Morik\n  - [[Paper]](https://sfb876.tu-dortmund.de/PublicPublicationFiles/buschjaeger_2018a.pdf)\n\n- **Finding Influential Training Samples for Gradient Boosted Decision Trees (ICML 2018)**\n  - Boris Sharchilev, Yury Ustinovskiy, Pavel Serdyukov, Maarten de Rijke\n  - [[Paper]](https://arxiv.org/abs/1802.06640)\n  - [[Code]](https://github.com/bsharchilev/influence_boosting)\n\n- **Learning Optimal Decision Trees with SAT (IJCAI 2018)**\n  - Nina Narodytska, Alexey Ignatiev, Filipe Pereira, João Marques-Silva\n  - [[Paper]](https://www.ijcai.org/proceedings/2018/0189.pdf)\n\n- **Extremely Fast Decision Tree (KDD 2018)**\n  - Chaitanya Manapragada, Geoffrey I. Webb, Mahsa Salehi\n  - [[Paper]](https://arxiv.org/abs/1802.08780)\n  - [[Code]](https://github.com/doubleplusplus/incremental_decision_tree-CART-Random_Forest_python)\n  \n- **RapidScorer: Fast Tree Ensemble Evaluation by Maximizing Compactness in Data Level Parallelization (KDD 2018)**\n  - Ting Ye, Hucheng Zhou, Will Y. Zou, Bin Gao, Ruofei Zhang\n  - [[Paper]](http://ai.stanford.edu/~wzou/kdd_rapidscorer.pdf)\n  \n- **CatBoost: Unbiased Boosting with Categorical Features (NIPS 2018)**\n  - Liudmila Prokhorenkova, Gleb Gusev, Aleksandr Vorobev, Anna Veronika Dorogush, Andrey Gulin\n  - [[Paper]](https://papers.nips.cc/paper/7898-catboost-unbiased-boosting-with-categorical-features.pdf)\n  - [[Code]](https://catboost.ai/)\n  \n- **Active Learning for Non-Parametric Regression Using Purely Random Trees (NIPS 2018)**\n  - Jack Goetz, Ambuj Tewari, Paul Zimmerman\n  - [[Paper]](https://papers.nips.cc/paper/7520-active-learning-for-non-parametric-regression-using-purely-random-trees.pdf)\n\n- **Alternating Optimization of Decision Trees with Application to Learning Sparse Oblique Trees (NIPS 2018)**\n  - Miguel Á. Carreira-Perpiñán, Pooya Tavallali\n  - [[Paper]](https://papers.nips.cc/paper/7397-alternating-optimization-of-decision-trees-with-application-to-learning-sparse-oblique-trees)\n\n- **Multi-Layered Gradient Boosting Decision Trees (NIPS 2018)**\n  - Ji Feng, Yang Yu, Zhi-Hua Zhou\n  - [[Paper]](https://papers.nips.cc/paper/7614-multi-layered-gradient-boosting-decision-trees.pdf)\n  - [[Code]](https://github.com/kingfengji/mGBDT)\n  \n- **Transparent Tree Ensembles (SIGIR 2018)**\n  - Alexander Moore, Vanessa Murdock, Yaxiong Cai, Kristine Jones\n  - [[Paper]](http://delivery.acm.org/10.1145/3220000/3210151/p1241-moore.pdf?ip=129.215.164.203\u0026id=3210151\u0026acc=ACTIVE%20SERVICE\u0026key=C2D842D97AC95F7A%2EEB9E991028F4E1F1%2E4D4702B0C3E38B35%2E4D4702B0C3E38B35\u0026__acm__=1559054892_a29816c683aa83a0ce0fbb777c68daba)\n\n- **Privacy-aware Ranking with Tree Ensembles on the Cloud (SIGIR 2018)**\n  - Shiyu Ji, Jinjin Shao, Daniel Agun, Tao Yang\n  - [[Paper]](https://sites.cs.ucsb.edu/projects/ds/sigir18.pdf)\n\n## 2017\n- **Strategic Sequences of Arguments for Persuasion Using Decision Trees (AAAI 2017)**\n  - Emmanuel Hadoux, Anthony Hunter\n  - [[Paper]](http://www0.cs.ucl.ac.uk/staff/a.hunter/papers/aaai17.pdf)\n\n- **BoostVHT: Boosting Distributed Streaming Decision Trees (CIKM 2017)**\n  - Theodore Vasiloudis, Foteini Beligianni, Gianmarco De Francisci Morales\n  - [[Paper]](https://melmeric.files.wordpress.com/2010/05/boostvht-boosting-distributed-streaming-decision-trees.pdf)\n\n- **Latency Reduction via Decision Tree Based Query Construction (CIKM 2017)**\n  - Aman Grover, Dhruv Arya, Ganesh Venkataraman\n  - [[Paper]](https://dl.acm.org/citation.cfm?id=3132865)\n\n- **Enumerating Distinct Decision Trees (ICML 2017)**\n  - Salvatore Ruggieri\n  - [[Paper]](http://proceedings.mlr.press/v70/ruggieri17a/ruggieri17a.pdf)\n\n- **Gradient Boosted Decision Trees for High Dimensional Sparse Output (ICML 2017)**\n  - Si Si, Huan Zhang, S. Sathiya Keerthi, Dhruv Mahajan, Inderjit S. Dhillon, Cho-Jui Hsieh\n  - [[Paper]](http://proceedings.mlr.press/v70/si17a.html)\n  - [[Code]](https://github.com/springdaisy/GBDT)\n\n- **Consistent Feature Attribution for Tree Ensembles (ICML 2017)**\n  - Scott M. Lundberg, Su-In Lee\n  - [[Paper]](https://arxiv.org/abs/1706.06060)\n  - [[Code]](https://github.com/slundberg/shap)\n\n- **Extremely Fast Decision Tree Mining for Evolving Data Streams (KDD 2017)**\n  - Albert Bifet, Jiajin Zhang, Wei Fan, Cheng He, Jianfeng Zhang, Jianfeng Qian, Geoff Holmes, Bernhard Pfahringer\n  - [[Paper]](https://core.ac.uk/download/pdf/151040580.pdf)\n  \n- **CatBoost: Gradient Boosting with Categorical Features Support (NIPS 2017)**\n  - Anna Veronika Dorogush, Vasily Ershov, Andrey Gulin\n  - [[Paper]](https://arxiv.org/abs/1810.11363)\n  - [[Code]](https://catboost.ai/)\n\n- **LightGBM: A Highly Efficient Gradient Boosting Decision Tree (NIPS 2017)**\n  - Guolin Ke, Qi Meng, Thomas Finley, Taifeng Wang, Wei Chen, Weidong Ma, Qiwei Ye, Tie-Yan Liu\n  - [[Paper]](https://papers.nips.cc/paper/6907-lightgbm-a-highly-efficient-gradient-boosting-decision-tree)\n  - [[Code]](https://lightgbm.readthedocs.io/en/latest/)\n\n- **Variable Importance Using Decision Trees (NIPS 2017)**\n  - Jalil Kazemitabar, Arash Amini, Adam Bloniarz, Ameet S. Talwalkar\n  - [[Paper]](https://papers.nips.cc/paper/6646-variable-importance-using-decision-trees)\n\n- **A Unified Approach to Interpreting Model Predictions (NIPS 2017)**\n  - Scott M. Lundberg, Su-In Lee\n  - [[Paper]](https://papers.nips.cc/paper/7062-a-unified-approach-to-interpreting-model-predictions)\n  - [[Code]](https://github.com/slundberg/shap)\n\n- **Pruning Decision Trees via Max-Heap Projection (SDM 2017)**\n  - Zhi Nie, Binbin Lin, Shuai Huang, Naren Ramakrishnan, Wei Fan, Jieping Ye\n  - [[Paper]](https://www.researchgate.net/publication/317485748_Pruning_Decision_Trees_via_Max-Heap_Projection)\n\n- **A Practical Method for Solving Contextual Bandit Problems Using Decision Trees (UAI 2017)**\n  - Adam N. Elmachtoub, Ryan McNellis, Sechan Oh, Marek Petrik\n  - [[Paper]](https://arxiv.org/abs/1706.04687)\n\n- **Complexity of Solving Decision Trees with Skew-Symmetric Bilinear Utility (UAI 2017)**\n  - Hugo Gilbert, Olivier Spanjaard\n  - [[Paper]](http://auai.org/uai2017/proceedings/papers/64.pdf)\n  \n- **GB-CENT: Gradient Boosted Categorical Embedding and Numerical Trees (WWW 2017)**\n  - Qian Zhao, Yue Shi, Liangjie Hong\n  - [[Paper]](http://papers.www2017.com.au.s3-website-ap-southeast-2.amazonaws.com/proceedings/p1311.pdf)\n\n## 2016\n- **Sparse Perceptron Decision Tree for Millions of Dimensions (AAAI 2016)**\n  - Weiwei Liu, Ivor W. Tsang\n  - [[Paper]](https://aaai.org/ocs/index.php/AAAI/AAAI16/paper/view/12111)\n\n- **Learning Online Smooth Predictors for Realtime Camera Planning Using Recurrent Decision Trees (CVPR 2016)**\n  - Jianhui Chen, Hoang Minh Le, Peter Carr, Yisong Yue, James J. Little\n  - [[Paper]](http://hoangle.info/papers/cvpr2016_online_smooth_long.pdf)\n\n- **Online Learning with Bayesian Classification Trees (CVPR 2016)**\n  - Samuel Rota Bulò, Peter Kontschieder\n  - [[Paper]](http://www.dsi.unive.it/~srotabul/files/publications/CVPR2016.pdf)\n\n- **Accurate Robust and Efficient Error Estimation for Decision Trees (ICML 2016)**\n  - Lixin Fan\n  - [[Paper]](http://proceedings.mlr.press/v48/fan16.pdf)\n\n- **Meta-Gradient Boosted Decision Tree Model for Weight and Target Learning (ICML 2016)**\n  - Yury Ustinovskiy, Valentina Fedorova, Gleb Gusev, Pavel Serdyukov\n  - [[Paper]](http://proceedings.mlr.press/v48/ustinovskiy16.html)\n\n- **Boosted Decision Tree Regression Adjustment for Variance Reduction in Online Controlled Experiments (KDD 2016)**\n  - Alexey Poyarkov, Alexey Drutsa, Andrey Khalyavin, Gleb Gusev, Pavel Serdyukov\n  - [[Paper]](https://www.kdd.org/kdd2016/papers/files/adf0653-poyarkovA.pdf)\n  \n- **XGBoost: A Scalable Tree Boosting System (KDD 2016)**\n  - Tianqi Chen, Carlos Guestrin\n  - [[Paper]](https://www.kdd.org/kdd2016/papers/files/rfp0697-chenAemb.pdf)\n  - [[Code]](https://xgboost.readthedocs.io/en/latest/)\n\n- **Yggdrasil: An Optimized System for Training Deep Decision Trees at Scale (NIPS 2016)**\n  - Firas Abuzaid, Joseph K. Bradley, Feynman T. Liang, Andrew Feng, Lee Yang, Matei Zaharia, Ameet S. Talwalkar\n  - [[Paper]](https://papers.nips.cc/paper/6366-yggdrasil-an-optimized-system-for-training-deep-decision-trees-at-scale)\n\n- **A Communication-Efficient Parallel Algorithm for Decision Tree (NIPS 2016)**\n  - Qi Meng, Guolin Ke, Taifeng Wang, Wei Chen, Qiwei Ye, Zhiming Ma, Tie-Yan Liu\n  - [[Paper]](https://arxiv.org/abs/1611.01276)\n  - [[Code]](https://github.com/microsoft/LightGBM/blob/master/docs/Features.rst)\n\n- **Exploiting CPU SIMD Extensions to Speed-up Document Scoring with Tree Ensembles (SIGIR 2016)**\n  - Claudio Lucchese, Franco Maria Nardini, Salvatore Orlando, Raffaele Perego, Nicola Tonellotto, Rossano Venturini\n  - [[Paper]](http://pages.di.unipi.it/rossano/wp-content/uploads/sites/7/2016/07/SIGIR16a.pdf)\n  - [[Code]](https://github.com/hpclab/vectorized-quickscorer)\n\n- **Post-Learning Optimization of Tree Ensembles for Efficient Ranking (SIGIR 2016)**\n  - Claudio Lucchese, Franco Maria Nardini, Salvatore Orlando, Raffaele Perego, Fabrizio Silvestri, Salvatore Trani\n  - [[Paper]](https://www.researchgate.net/publication/305081572_Post-Learning_Optimization_of_Tree_Ensembles_for_Efficient_Ranking)\n  - [[Code]](https://github.com/hpclab/quickrank)\n\n## 2015\n- **Particle Gibbs for Bayesian Additive Regression Trees (AISTATS 2015)**\n  - Balaji Lakshminarayanan, Daniel M. Roy, Yee Whye Teh\n  - [[Paper]](https://arxiv.org/abs/1502.04622)\n\n- **DART: Dropouts Meet Multiple Additive Regression Trees (AISTATS 2015)**\n  - Korlakai Vinayak Rashmi, Ran Gilad-Bachrach\n  - [[Paper]](https://arxiv.org/abs/1505.01866)\n  - [[Code]](https://xgboost.readthedocs.io/en/latest/)\n\n- **Single Target Tracking Using Adaptive Clustered Decision Trees and Dynamic Multi-level Appearance Models (CVPR 2015)**\n  - Jingjing Xiao, Rustam Stolkin, Ales Leonardis\n  - [[Paper]](https://www.cv-foundation.org/openaccess/content_cvpr_2015/app/3B_058.pdf)\n\n- **Face Alignment Using Cascade Gaussian Process Regression Trees (CVPR 2015)**\n  - Donghoon Lee, Hyunsin Park, Chang Dong Yoo\n  - [[Paper]](https://slsp.kaist.ac.kr/paperdata/Face_Alignment_Using.pdf)\n  - [[Code]](https://github.com/donghoonlee04/cGPRT)\n\n- **Tracking-by-Segmentation with Online Gradient Boosting Decision Tree (ICCV 2015)**\n  - Jeany Son, Ilchae Jung, Kayoung Park, Bohyung Han\n  - [[Paper]](https://www.cv-foundation.org/openaccess/content_iccv_2015/papers/Son_Tracking-by-Segmentation_With_Online_ICCV_2015_paper.pdf)\n\n- **Entropy Evaluation Based on Confidence Intervals of Frequency Estimates : Application to the Learning of Decision Trees (ICML 2015)**\n  - Mathieu Serrurier, Henri Prade\n  - [[Paper]](http://proceedings.mlr.press/v37/serrurier15.pdf)\n  \n- **Large-scale Distributed Dependent Nonparametric Trees (ICML 2015)**\n  - Zhiting Hu, Qirong Ho, Avinava Dubey, Eric P. Xing\n  - [[Paper]](https://www.cs.cmu.edu/~zhitingh/data/icml15hu.pdf)\n\n- **Optimal Action Extraction for Random Forests and Boosted Trees (KDD 2015)**\n  - Zhicheng Cui, Wenlin Chen, Yujie He, Yixin Chen\n  - [[Paper]](https://www.cse.wustl.edu/~ychen/public/OAE.pdf)\n\n- **A Decision Tree Framework for Spatiotemporal Sequence Prediction (KDD 2015)**\n  - Taehwan Kim, Yisong Yue, Sarah L. Taylor, Iain A. Matthews\n  - [[Paper]](http://www.yisongyue.com/publications/kdd2015_ssw_dt.pdf)\n\n- **Efficient Non-greedy Optimization of Decision Trees (NIPS 2015)**\n  - Mohammad Norouzi, Maxwell D. Collins, Matthew Johnson, David J. Fleet, Pushmeet Kohli\n  - [[Paper]](https://arxiv.org/abs/1511.04056)\n  \n- **QuickScorer: A Fast Algorithm to Rank Documents with Additive Ensembles of Regression Trees (SIGIR 2015)**\n  - Claudio Lucchese, Franco Maria Nardini, Salvatore Orlando, Raffaele Perego, Nicola Tonellotto, Rossano Venturini\n  - [[Paper]](http://pages.di.unipi.it/rossano/wp-content/uploads/sites/7/2015/11/sigir15.pdf)\n  - [[Code]](https://github.com/hpclab/quickrank)\n\n## 2014\n\n- **A Mixtures-of-Trees Framework for Multi-Label Classification (CIKM 2014)**\n  - Charmgil Hong, Iyad Batal, Milos Hauskrecht\n  - [[Paper]](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4410801/)\n  \n- **On Building Decision Trees from Large-scale Data in Applications of On-line Advertising (CIKM 2014)**\n  - Shivaram Kalyanakrishnan, Deepthi Singh, Ravi Kant\n  - [[Paper]](https://www.cse.iitb.ac.in/~shivaram/papers/ksk_cikm_2014.pdf)\n\n- **Fast Supervised Hashing with Decision Trees for High-Dimensional Data (CVPR 2014)**\n  - Guosheng Lin, Chunhua Shen, Qinfeng Shi, Anton van den Hengel, David Suter\n  - [[Paper]](https://arxiv.org/abs/1404.1561)\n\n- **One Millisecond Face Alignment with an Ensemble of Regression Trees (CVPR 2014)**\n  - Vahid Kazemi, Josephine Sullivan\n  - [[Paper]](https://www.researchgate.net/publication/264419855_One_Millisecond_Face_Alignment_with_an_Ensemble_of_Regression_Trees)\n  \n- **The return of AdaBoost.MH: multi-class Hamming trees (ICLR 2014)**\n  - Balázs Kégl\n  - [[Paper]](https://arxiv.org/pdf/1312.6086.pdf)\n\n- **Diagnosis Determination: Decision Trees Optimizing Simultaneously Worst and Expected Testing Cost (ICML 2014)**\n  - Ferdinando Cicalese, Eduardo Sany Laber, Aline Medeiros Saettler\n  - [[Paper]](https://pdfs.semanticscholar.org/47ae/852f83b76f95b27ab00308d04f6020bdf71f.pdf)\n  \n- **Learning Multiple-Question Decision Trees for Cold-Start Recommendation (WSDM 2013)**\n  - Mingxuan Sun, Fuxin Li, Joonseok Lee, Ke Zhou, Guy Lebanon, Hongyuan Zha\n  - [[Paper]](http://www.joonseok.net/papers/coldstart.pdf)\n\n## 2013\n- **Weakly Supervised Learning of Image Partitioning Using Decision Trees with Structured Split Criteria (ICCV 2013)**\n  - Christoph N. Straehle, Ullrich Köthe, Fred A. Hamprecht\n  - [[Paper]](https://ieeexplore.ieee.org/document/6751340)\n\n- **Revisiting Example Dependent Cost-Sensitive Learning with Decision Trees (ICCV 2013)**\n  - Oisin Mac Aodha, Gabriel J. Brostow\n  - [[Paper]](https://ieeexplore.ieee.org/document/6751133)\n\n- **Conformal Prediction Using Decision Trees (ICDM 2013)**\n  - Ulf Johansson, Henrik Boström, Tuve Löfström\n  - [[Paper]](https://ieeexplore.ieee.org/abstract/document/6729517)\n\n- **Focal-Test-Based Spatial Decision Tree Learning: A Summary of Results (ICDM 2013)**\n  - Zhe Jiang, Shashi Shekhar, Xun Zhou, Joseph K. Knight, Jennifer Corcoran\n  - [[Paper]](https://pdfs.semanticscholar.org/f28e/df8d9eed76e4ce97cb6bd4182d590547be5e.pdf)\n\n- **Top-down Particle Filtering for Bayesian Decision Trees (ICML 2013)**\n  - Balaji Lakshminarayanan, Daniel M. Roy, Yee Whye Teh\n  - [[Paper]](https://arxiv.org/abs/1303.0561)\n\n- **Quickly Boosting Decision Trees - Pruning Underachieving Features Early (ICML 2013)**\n  - Ron Appel, Thomas J. Fuchs, Piotr Dollár, Pietro Perona\n  - [[Paper]](http://proceedings.mlr.press/v28/appel13.pdf)\n\n- **Knowledge Compilation for Model Counting: Affine Decision Trees (IJCAI 2013)**\n  - Frédéric Koriche, Jean-Marie Lagniez, Pierre Marquis, Samuel Thomas\n  - [[Paper]](https://www.researchgate.net/publication/262398921_Knowledge_Compilation_for_Model_Counting_Affine_Decision_Trees)\n  \n- **Understanding Variable Importances in Forests of Randomized Trees (NIPS 2013)**\n  - Gilles Louppe, Louis Wehenkel, Antonio Sutera, Pierre Geurts\n  - [[Paper]](https://papers.nips.cc/paper/4928-understanding-variable-importances-in-forests-of-randomized-trees)\n\n- **Regression-tree Tuning in a Streaming Setting (NIPS 2013)**\n  - Samory Kpotufe, Francesco Orabona\n  - [[Paper]](https://papers.nips.cc/paper/4898-regression-tree-tuning-in-a-streaming-setting)\n\n- **Learning Max-Margin Tree Predictors (UAI 2013)**\n  - Ofer Meshi, Elad Eban, Gal Elidan, Amir Globerson\n  - [[Paper]](https://ttic.uchicago.edu/~meshi/papers/mtreen.pdf)\n\n## 2012\n- **Regression Tree Fields - An Efficient, Non-parametric Approach to Image Labeling Problems (CVPR 2012)**\n  - Jeremy Jancsary, Sebastian Nowozin, Toby Sharp, Carsten Rother\n  - [[Paper]](http://www.nowozin.net/sebastian/papers/jancsary2012rtf.pdf)\n\n- **ConfDTree: Improving Decision Trees Using Confidence Intervals (ICDM 2012)**\n  - Gilad Katz, Asaf Shabtai, Lior Rokach, Nir Ofek\n  - [[Paper]](https://ieeexplore.ieee.org/document/6413889)\n\n- **Improved Information Gain Estimates for Decision Tree Induction (ICML 2012)**\n  - Sebastian Nowozin\n  - [[Paper]](https://arxiv.org/abs/1206.4620)\n\n- **Learning Partially Observable Models Using Temporally Abstract Decision Trees (NIPS 2012)**\n  - Erik Talvitie\n  - [[Paper]](https://papers.nips.cc/paper/4662-learning-partially-observable-models-using-temporally-abstract-decision-trees)\n  \n- **Subtree Replacement in Decision Tree Simplification (SDM 2012)**\n  - Salvatore Ruggieri\n  - [[Paper]](http://pages.di.unipi.it/ruggieri/Papers/sdm2012.pdf)\n\n## 2011\n- **Incorporating Boosted Regression Trees into Ecological Latent Variable Models (AAAI 2011)**\n  - Rebecca A. Hutchinson, Li-Ping Liu, Thomas G. Dietterich\n  - [[Paper]](https://www.aaai.org/ocs/index.php/AAAI/AAAI11/paper/viewFile/3711/4086)\n\n- **Syntactic Decision Tree LMs: Random Selection or Intelligent Design (EMNLP 2011)**\n  - Denis Filimonov, Mary P. Harper\n  - [[Paper]](https://www.aclweb.org/anthology/D11-1064)\n  \n- **Decision Tree Fields (ICCV 2011)**\n  - Sebastian Nowozin, Carsten Rother, Shai Bagon, Toby Sharp, Bangpeng Yao, Pushmeet Kohli\n  - [[Paper]](https://www.microsoft.com/en-us/research/wp-content/uploads/2016/11/nrbsyk_iccv11.pdf)\n\n- **Confidence in Predictions from Random Tree Ensembles (ICDM 2011)**\n  - Siddhartha Bhattacharyya\n  - [[Paper]](https://link.springer.com/article/10.1007/s10115-012-0600-z)\n\n- **Speeding-Up Hoeffding-Based Regression Trees With Options (ICML 2011)**\n  - Elena Ikonomovska, João Gama, Bernard Zenko, Saso Dzeroski\n  - [[Paper]](https://icml.cc/Conferences/2011/papers/349_icmlpaper.pdf)\n  \n- **Density Estimation Trees (KDD 2011)**\n  - Parikshit Ram, Alexander G. Gray\n  - [[Paper]](https://mlpack.org/papers/det.pdf)\n  \n- **Bagging Gradient-Boosted Trees for High Precision, Low Variance Ranking Models (SIGIR 2011)**\n  - Yasser Ganjisaffar, Rich Caruana, Cristina Videira Lopes\n  - [[Paper]](http://www.ccs.neu.edu/home/vip/teach/MLcourse/4_boosting/materials/bagging_lmbamart_jforests.pdf)\n\n- **On the Complexity of Decision Making in Possibilistic Decision Trees (UAI 2011)**\n  - Hélène Fargier, Nahla Ben Amor, Wided Guezguez\n  - [[Paper]](https://dslpitt.org/uai/papers/11/p203-fargier.pdf)\n\n- **Adaptive Bootstrapping of Recommender Systems Using Decision Trees (WSDM 2011)**\n  - Nadav Golbandi, Yehuda Koren, Ronny Lempel\n  - [[Paper]](https://dl.acm.org/citation.cfm?id=1935910)\n\n- **Parallel Boosted Regression Trees for Web Search Ranking (WWW 2011)**\n  - Stephen Tyree, Kilian Q. Weinberger, Kunal Agrawal, Jennifer Paykin\n  - [[Paper]](http://www.cs.cornell.edu/~kilian/papers/fr819-tyreeA.pdf)\n\n## 2010\n- **Discrimination Aware Decision Tree Learning (ICDM 2010)**\n  - Faisal Kamiran, Toon Calders, Mykola Pechenizkiy\n  - [[Paper]](https://www.win.tue.nl/~mpechen/publications/pubs/KamiranICDM2010.pdf)\n\n- **Decision Trees for Uplift Modeling (ICDM 2010)**\n  - Piotr Rzepakowski, Szymon Jaroszewicz\n  - [[Paper]](https://core.ac.uk/download/pdf/81899141.pdf)\n\n- **Learning Markov Network Structure with Decision Trees (ICDM 2010)**\n  - Daniel Lowd, Jesse Davis\n  - [[Paper]](https://ix.cs.uoregon.edu/~lowd/icdm10lowd.pdf)\n\n- **Multivariate Dyadic Regression Trees for Sparse Learning Problems (NIPS 2010)**\n  - Han Liu, Xi Chen\n  - [[Paper]](https://papers.nips.cc/paper/4178-multivariate-dyadic-regression-trees-for-sparse-learning-problems.pdf)\n  \n- **Fast and Accurate Gene Prediction by Decision Tree Classification (SDM 2010)**\n  - Rong She, Jeffrey Shih-Chieh Chu, Ke Wang, Nansheng Chen\n  - [[Paper]](http://www.sfu.ca/~chenn/genBlastDT_sdm.pdf)\n\n- **A Robust Decision Tree Algorithm for Imbalanced Data Sets (SDM 2010)**\n  - Wei Liu, Sanjay Chawla, David A. Cieslak, Nitesh V. Chawla\n  - [[Paper]](https://www3.nd.edu/~nchawla/papers/SDM10.pdf)\n\n## 2009\n- **Stochastic Gradient Boosted Distributed Decision Trees (CIKM 2009)**\n  - Jerry Ye, Jyh-Herng Chow, Jiang Chen, Zhaohui Zheng\n  - [[Paper]](https://dl.acm.org/citation.cfm?id=1646301)\n  \n- **Feature Selection for Ranking Using Boosted Trees (CIKM 2009)**\n  - Feng Pan, Tim Converse, David Ahn, Franco Salvetti, Gianluca Donato\n  - [[Paper]](http://www.francosalvetti.com/cikm09_camera2.pdf)\n  \n- **Thai Word Segmentation with Hidden Markov Model and Decision Tree (PAKDD 2009)**\n  - Poramin Bheganan, Richi Nayak, Yue Xu\n  - [[Paper]](https://link.springer.com/chapter/10.1007/978-3-642-01307-2_10)\n\n- **Parameter Estimdation in Semi-Random Decision Tree Ensembling on Streaming Data (PAKDD 2009)**\n  - Pei-Pei Li, Qianhui Liang, Xindong Wu, Xuegang Hu\n  - [[Paper]](https://link.springer.com/chapter/10.1007/978-3-642-01307-2_35)\n\n- **DTU: A Decision Tree for Uncertain Data (PAKDD 2009)**\n  - Biao Qin, Yuni Xia, Fang Li\n  - [[Paper]](https://link.springer.com/chapter/10.1007/978-3-642-01307-2_4)\n\n## 2008\n- **Predicting Future Decision Trees from Evolving Data (ICDM 2008)**\n  - Mirko Böttcher, Martin Spott, Rudolf Kruse\n  - [[Paper]](https://ieeexplore.ieee.org/document/4781098)\n\n- **Bayes Optimal Classification for Decision Trees (ICML 2008)**\n  - Siegfried Nijssen\n  - [[Paper]](http://icml2008.cs.helsinki.fi/papers/455.pdf)\n  \n- **A New Credit Scoring Method Based on Rough Sets and Decision Tree (PAKDD 2008)**\n  - XiYue Zhou, Defu Zhang, Yi Jiang\n  - [[Paper]](https://link.springer.com/chapter/10.1007/978-3-540-68125-0_117)\n\n- **A Comparison of Different Off-Centered Entropies to Deal with Class Imbalance for Decision Trees (PAKDD 2008)**\n  - Philippe Lenca, Stéphane Lallich, Thanh-Nghi Do, Nguyen-Khang Pham\n  - [[Paper]](https://link.springer.com/chapter/10.1007/978-3-540-68125-0_59)\n\n- **BOAI: Fast Alternating Decision Tree Induction Based on Bottom-Up Evaluation (PAKDD 2008)**\n  - Bishan Yang, Tengjiao Wang, Dongqing Yang, Lei Chang\n  - [[Paper]](https://link.springer.com/chapter/10.1007/978-3-540-68125-0_36)\n\n- **A General Framework for Estimating Similarity of Datasets and Decision Trees: Exploring Semantic Similarity of Decision Trees (SDM 2008)**\n  - Irene Ntoutsi, Alexandros Kalousis, Yannis Theodoridis\n  - [[Paper]](https://www.researchgate.net/publication/220907047_A_general_framework_for_estimating_similarity_of_datasets_and_decision_trees_exploring_semantic_similarity_of_decision_trees)\n\n- **ROC-tree: A Novel Decision Tree Induction Algorithm Based on Receiver Operating Characteristics to Classify Gene Expression Data (SDM 2008)**\n  - M. Maruf Hossain, Md. Rafiul Hassan, James Bailey\n  - [[Paper]](https://pdfs.semanticscholar.org/bd80/db2f0903169b7611d34b2cc85f60a736375d.pdf)\n\n## 2007\n\n- **Tree-based Classifiers for Bilayer Video Segmentation (CVPR 2007)**\n  - Pei Yin, Antonio Criminisi, John M. Winn, Irfan A. Essa\n  - [[Paper]](https://ieeexplore.ieee.org/document/4270033)\n\n- **Additive Groves of Regression Trees (ECML 2007)**\n  - Daria Sorokina, Rich Caruana, Mirek Riedewald\n  - [[Paper]](http://additivegroves.net/papers/groves.pdf)\n\n- **Decision Tree Instability and Active Learning (ECML 2007)**\n  - Kenneth Dwyer, Robert Holte\n  - [[Paper]](https://webdocs.cs.ualberta.ca/~holte/Publications/ecml07.pdf)\n\n- **Ensembles of Multi-Objective Decision Trees (ECML 2007)**\n  - Dragi Kocev, Celine Vens, Jan Struyf, Saso Dzeroski\n  - [[Paper]](https://link.springer.com/chapter/10.1007/978-3-540-74958-5_61)\n\n- **Seeing the Forest Through the Trees: Learning a Comprehensible Model from an Ensemble (ECML 2007)**\n  - Anneleen Van Assche, Hendrik Blockeel\n  - [[Paper]](http://ftp.cs.wisc.edu/machine-learning/shavlik-group/ilp07wip/ilp07_assche.pdf)\n\n- **Sample Compression Bounds for Decision Trees (ICML 2007)**\n  - Mohak Shah\n  - [[Paper]](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.331.9136\u0026rep=rep1\u0026type=pdf)\n\n- **A Tighter Error Bound for Decision Tree Learning Using PAC Learnability (IJCAI 2007)**\n  - Chaithanya Pichuka, Raju S. Bapi, Chakravarthy Bhagvati, Arun K. Pujari, Bulusu Lakshmana Deekshatulu\n  - [[Paper]](https://www.ijcai.org/Proceedings/07/Papers/163.pdf)\n\n- **Keep the Decision Tree and Estimate the Class Probabilities Using its Decision Boundary (IJCAI 2007)**\n  - Isabelle Alvarez, Stephan Bernard, Guillaume Deffuant\n  - [[Paper]](https://www.ijcai.org/Proceedings/07/Papers/104.pdf)\n\n- **Real Boosting a la Carte with an Application to Boosting Oblique Decision Tree (IJCAI 2007)**\n  - Claudia Henry, Richard Nock, Frank Nielsen\n  - [[Paper]](https://www.ijcai.org/Proceedings/07/Papers/135.pdf)\n\n- **Scalable Look-ahead Linear Regression Trees (KDD 2007)**\n  - David S. Vogel, Ognian Asparouhov, Tobias Scheffer\n  - [[Paper]](https://www.cs.uni-potsdam.de/ml/publications/kdd2007.pdf)\n\n- **Mining Optimal Decision Trees from Itemset Lattices (KDD 2007)**\n  - Siegfried Nijssen, Élisa Fromont\n  - [[Paper]](https://hal.archives-ouvertes.fr/hal-00372011/document)\n  \n- **A Hybrid Multi-group Privacy-Preserving Approach for Building Decision Trees (PAKDD 2007)**\n  - Zhouxuan Teng, Wenliang Du\n  - [[Paper]](https://link.springer.com/chapter/10.1007/978-3-540-71701-0_30)\n\n## 2006\n- **Decision Tree Methods for Finding Reusable MDP Homomorphisms (AAAI 2006)**\n  - Alicia P. Wolfe, Andrew G. Barto\n  - [[Paper]](https://www.aaai.org/Papers/AAAI/2006/AAAI06-085.pdf)\n\n- **A Fast Decision Tree Learning Algorithm (AAAI 2006)**\n  - Jiang Su, Harry Zhang\n  - [[Paper]](http://www.cs.unb.ca/~hzhang/publications/AAAI06.pdf)\n\n- **Anytime Induction of Decision Trees: An Iterative Improvement Approach (AAAI 2006)**\n  - Saher Esmeir, Shaul Markovitch\n  - [[Paper]](https://www.aaai.org/Papers/AAAI/2006/AAAI06-056.pdf)\n\n- **When a Decision Tree Learner Has Plenty of Time (AAAI 2006)**\n  - Saher Esmeir, Shaul Markovitch\n  - [[Paper]](https://www.aaai.org/Papers/AAAI/2006/AAAI06-259.pdf)\n\n- **Decision Trees for Functional Variables (ICDM 2006)**\n  - Suhrid Balakrishnan, David Madigan\n  - [[Paper]](http://archive.dimacs.rutgers.edu/Research/MMS/PAPERS/fdt17.pdf)\n  \n- **Cost-Sensitive Decision Tree Learning for Forensic Classification (ECML 2006)**\n  - Jason V. Davis, Jungwoo Ha, Christopher J. Rossbach, Hany E. Ramadan, Emmett Witchel\n  - [[Paper]](https://www.cs.utexas.edu/users/witchel/pubs/davis-ecml06.pdf)\n\n- **Improving the Ranking Performance of Decision Trees (ECML 2006)**\n  - Bin Wang, Harry Zhang\n  - [[Paper]](https://link.springer.com/chapter/10.1007/11871842_44)\n\n- **A General Framework for Accurate and Fast Regression by Data Summarization in Random Decision Trees (KDD 2006)**\n  - Wei Fan, Joe McCloskey, Philip S. Yu\n  - [[Paper]](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.442.2004\u0026rep=rep1\u0026type=pdf)\n  \n- **Constructing Decision Trees for Graph-Structured Data by Chunkingless Graph-Based Induction (PAKDD 2006)**\n  - Phu Chien Nguyen, Kouzou Ohara, Akira Mogi, Hiroshi Motoda, Takashi Washio\n  - [[Paper]](http://www.ar.sanken.osaka-u.ac.jp/~motoda/papers/pakdd06.pdf)\n\n- **Variable Randomness in Decision Tree Ensembles (PAKDD 2006)**\n  - Fei Tony Liu, Kai Ming Ting\n  - [[Paper]](https://link.springer.com/chapter/10.1007/11731139_12)\n\n- **Generalized Conditional Entropy and a Metric Splitting Criterion for Decision Trees (PAKDD 2006)**\n  - Dan A. Simovici, Szymon Jaroszewicz\n  - [[Paper]](https://www.researchgate.net/profile/Szymon_Jaroszewicz/publication/220895184_Generalized_Conditional_Entropy_and_a_Metric_Splitting_Criterion_for_Decision_Trees/links/0fcfd50b1267f7b868000000/Generalized-Conditional-Entropy-and-a-Metric-Splitting-Criterion-for-Decision-Trees.pdf)\n\n- **Decision Trees for Hierarchical Multilabel Classification: A Case Study in Functional Genomics (PKDD 2006)**\n  - Hendrik Blockeel, Leander Schietgat, Jan Struyf, Saso Dzeroski, Amanda Clare\n  - [[Paper]](https://link.springer.com/chapter/10.1007/11871637_7)\n\n- **k-Anonymous Decision Tree Induction (PKDD 2006)**\n  - Arik Friedman, Assaf Schuster, Ran Wolff\n  - [[Paper]](http://www.cs.technion.ac.il/~arikf/online-publications/kADET06.pdf)\n\n## 2005\n- **Representing Conditional Independence Using Decision Trees (AAAI 2005)**\n  - Jiang Su, Harry Zhang\n  - [[Paper]](http://www.cs.unb.ca/~hzhang/publications/AAAI051SuJ.pdf)\n\n- **Use of Expert Knowledge for Decision Tree Pruning (AAAI 2005)**\n  - Jingfeng Cai, John Durkin\n  - [[Paper]](http://www.aaai.org/Papers/AAAI/2005/SA05-009.pdf)\n  \n- **Model Selection in Omnivariate Decision Trees (ECML 2005)**\n  - Olcay Taner Yildiz, Ethem Alpaydin\n  - [[Paper]](https://www.cmpe.boun.edu.tr/~ethem/files/papers/yildiz_ecml05.pdf)\n\n- **Combining Bias and Variance Reduction Techniques for Regression Trees (ECML 2005)**\n  - Yuk Lai Suen, Prem Melville, Raymond J. Mooney\n  - [[Paper]](http://www.cs.utexas.edu/users/ml/papers/bv-ecml-05.pdf)\n\n- **Simple Test Strategies for Cost-Sensitive Decision Trees (ECML 2005)**\n  - Shengli Sheng, Charles X. Ling, Qiang Yang\n  - [[Paper]](https://www.researchgate.net/publication/3297582_Test_strategies_for_cost-sensitive_decision_trees)\n\n- **Effective Estimation of Posterior Probabilities: Explaining the Accuracy of Randomized Decision Tree Approaches (ICDM 2005)**\n  - Wei Fan, Ed Greengrass, Joe McCloskey, Philip S. Yu, Kevin Drummey\n  - [[Paper]](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.218.9713\u0026rep=rep1\u0026type=pdf)\n\n- **Exploiting Informative Priors for Bayesian Classification and Regression Trees (IJCAI 2005)**\n  - Nicos Angelopoulos, James Cussens\n  - [[Paper]](https://www.ijcai.org/Proceedings/05/Papers/1013.pdf)\n\n- **Ranking Cases with Decision Trees: a Geometric Method that Preserves Intelligibility (IJCAI 2005)**\n  - Isabelle Alvarez, Stephan Bernard\n  - [[Paper]](https://www.ijcai.org/Proceedings/05/Papers/1502.pdf)\n  \n- **Maximizing Tree Diversity by Building Complete-Random Decision Trees (PAKDD 2005)**\n  - Fei Tony Liu, Kai Ming Ting, Wei Fan\n  - [[Paper]](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.218.7805\u0026rep=rep1\u0026type=pdf)\n\n- **Hybrid Cost-Sensitive Decision Tree (PKDD 2005)**\n  - Shengli Sheng, Charles X. Ling\n  - [[Paper]](https://cling.csd.uwo.ca/papers/pkdd05a.pdf)\n\n- **Tree2 - Decision Trees for Tree Structured Data (PKDD 2005)**\n  - Björn Bringmann, Albrecht Zimmermann\n  - [[Paper]](https://link.springer.com/chapter/10.1007/11564126_10)\n\n- **Building Decision Trees on Records Linked through Key References (SDM 2005)**\n  - Ke Wang, Yabo Xu, Philip S. Yu, Rong She\n  - [[Paper]](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.215.7181\u0026rep=rep1\u0026type=pdf)\n\n- **Decision Tree Induction in High Dimensional, Hierarchically Distributed Databases (SDM 2005)**\n  - Amir Bar-Or, Ran Wolff, Assaf Schuster, Daniel Keren\n  - [[Paper]](https://www.semanticscholar.org/paper/Decision-Tree-Induction-in-High-Dimensional%2C-Bar-Or-Wolff/90235fc35c27dae273681f7847c2b20ff37928a9)\n\n- **Boosted Decision Trees for Word Recognition in Handwritten Document Retrieval (SIGIR 2005)**\n  - Nicholas R. Howe, Toni M. Rath, R. Manmatha\n  - [[Paper]](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.152.1551\u0026rep=rep1\u0026type=pdf)\n\n## 2004\n- **On the Optimality of Probability Estimation by Random Decision Trees (AAAI 2004)**\n  - Wei Fan\n  - [[Paper]](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.447.2128\u0026rep=rep1\u0026type=pdf)\n\n- **Occam's Razor and a Non-Syntactic Measure of Decision Tree Complexity (AAAI 2004)**\n  - Goutam Paul\n  - [[Paper]](https://www.aaai.org/Papers/AAAI/2004/AAAI04-130.pdf)\n\n- **Using Emerging Patterns and Decision Trees in Rare-Class Classification (ICDM 2004)**\n  - Hamad Alhammady, Kotagiri Ramamohanarao\n  - [[Paper]](https://ieeexplore.ieee.org/abstract/document/1410299)\n\n- **Orthogonal Decision Trees (ICDM 2004)**\n  - Hillol Kargupta, Haimonti Dutta\n  - [[Paper]](https://www.csee.umbc.edu/~hillol/PUBS/odtree.pdf)\n\n- **Improving the Reliability of Decision Tree and Naive Bayes Learners (ICDM 2004)**\n  - David George Lindsay, Siân Cox\n  - [[Paper]](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.521.3127\u0026rep=rep1\u0026type=pdf)\n\n- **Communication Efficient Construction of Decision Trees Over Heterogeneously Distributed Data (ICDM 2004)**\n  - Chris Giannella, Kun Liu, Todd Olsen, Hillol Kargupta\n  - [[Paper]](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.79.7119\u0026rep=rep1\u0026type=pdf)\n\n- **Decision Tree Evolution Using Limited Number of Labeled Data Items from Drifting Data Streams (ICDM 2004)**\n  - Wei Fan, Yi-an Huang, Philip S. Yu\n  - [[Paper]](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.218.9450\u0026rep=rep1\u0026type=pdf)\n\n- **Lookahead-based Algorithms for Anytime Induction of Decision Trees (ICML 2004)**\n  - Saher Esmeir, Shaul Markovitch\n  - [[Paper]](http://www.cs.technion.ac.il/~shaulm/papers/pdf/Esmeir-Markovitch-icml2004.pdf)\n  \n- **Decision Trees with Minimal Costs (ICML 2004)**\n  - Charles X. Ling, Qiang Yang, Jianning Wang, Shichao Zhang\n  - [[Paper]](https://icml.cc/Conferences/2004/proceedings/papers/136.pdf)\n\n- **Training Conditional Random Fields via Gradient Tree Boosting (ICML 2004)**\n  - Thomas G. Dietterich, Adam Ashenfelter, Yaroslav Bulatov\n  - [[Paper]](http://web.engr.oregonstate.edu/~tgd/publications/ml2004-treecrf.pdf)\n\n- **Detecting Structural Metadata with Decision Trees and Transformation-Based Learning (NAACL 2004)**\n  - Joungbum Kim, Sarah E. Schwarm, Mari Ostendorf\n  - [[Paper]](https://www.aclweb.org/anthology/N04-1018)\n\n- **On the Adaptive Properties of Decision Trees (NIPS 2004)**\n  - Clayton D. Scott, Robert D. Nowak\n  - [[Paper]](https://papers.nips.cc/paper/2625-on-the-adaptive-properties-of-decision-trees.pdf)\n  \n- **A Metric Approach to Building Decision Trees Based on Goodman-Kruskal Association Index (PAKDD 2004)**\n  - Dan A. Simovici, Szymon Jaroszewicz\n  - [[Paper]](https://www.researchgate.net/publication/2906289_A_Metric_Approach_to_Building_Decision_Trees_Based_on_Goodman-Kruskal_Association_Index)\n\n## 2003\n- **Rademacher Penalization over Decision Tree Prunings (ECML 2003)**\n  - Matti Kääriäinen, Tapio Elomaa\n  - [[Paper]](https://www.researchgate.net/publication/221112653_Rademacher_Penalization_over_Decision_Tree_Prunings)\n  \n- **Ensembles of Cascading Trees (ICDM 2003)**\n  - Jinyan Li, Huiqing Liu\n  - [[Paper]](https://www.researchgate.net/publication/4047523_Ensembles_of_cascading_trees)\n\n- **Postprocessing Decision Trees to Extract Actionable Knowledge (ICDM 2003)**\n  - Qiang Yang, Jie Yin, Charles X. Ling, Tielin Chen\n  - [[Paper]](https://pdfs.semanticscholar.org/b2c6/ff54c7aeefc70820ff04a8fc8b804012c504.pdf)\n\n- **K-D Decision Tree: An Accelerated and Memory Efficient Nearest Neighbor Classifier (ICDM 2003)**\n  - Tomoyuki Shibata, Takekazu Kato, Toshikazu Wada\n  - [[Paper]](https://ieeexplore.ieee.org/abstract/document/1250997)\n\n- **Identifying Markov Blankets with Decision Tree Induction (ICDM 2003)**\n  - Lewis J. Frey, Douglas H. Fisher, Ioannis Tsamardinos, Constantin F. Aliferis, Alexander R. Statnikov\n  - [[Paper]](https://www.semanticscholar.org/paper/Identifying-Markov-Blankets-with-Decision-Tree-Frey-Fisher/1aa0b0ede22f3963c923ea320a8bed91ac5aafbf)\n\n- **Comparing Naive Bayes, Decision Trees, and SVM with AUC and Accuracy (ICDM 2003)**\n  - Jin Huang, Jingjing Lu, Charles X. Ling\n  - [[Paper]](https://pdfs.semanticscholar.org/8a73/74b98a9d94b8c01e996e72340f86a4327869.pdf)\n\n- **Boosting Lazy Decision Trees (ICML 2003)**\n  - Xiaoli Zhang Fern, Carla E. Brodley\n  - [[Paper]](https://www.aaai.org/Papers/ICML/2003/ICML03-026.pdf)\n\n- **Decision Tree with Better Ranking (ICML 2003)**\n  - Charles X. Ling, Robert J. Yan\n  - [[Paper]](https://www.aaai.org/Papers/ICML/2003/ICML03-064.pdf)\n\n- **Skewing: An Efficient Alternative to Lookahead for Decision Tree Induction (IJCAI 2003)**\n  - David Page, Soumya Ray\n  - [[Paper]](http://pages.cs.wisc.edu/~dpage/ijcai3.pdf)\n\n- **Efficient Decision Tree Construction on Streaming Data (KDD 2003)**\n  - Ruoming Jin, Gagan Agrawal\n  - [[Paper]](http://web.cse.ohio-state.edu/~agrawal.28/p/sigkdd03.pdf)\n\n- **PaintingClass: Interactive Construction Visualization and Exploration of Decision Trees (KDD 2003)**\n  - Soon Tee Teoh, Kwan-Liu Ma\n  - [[Paper]](https://www.researchgate.net/publication/220272011_PaintingClass_interactive_construction_visualization_and_exploration_of_decision_trees)\n\n- **Accurate Decision Trees for Mining High-Speed Data Streams (KDD 2003)**\n  - João Gama, Ricardo Rocha, Pedro Medas\n  - [[Paper]](http://staff.icar.cnr.it/manco/Teaching/2006/datamining/Esami2006/ArticoliSelezionatiDM/SEMINARI/Mining%20Data%20Streams/kdd03.pdf)\n\n- **Near-Minimax Optimal Classification with Dyadic Classification Trees (NIPS 2003)**\n  - Clayton D. Scott, Robert D. Nowak\n  - [[Paper]](http://nowak.ece.wisc.edu/nips03.pdf)\n  \n- **Improving Performance of Decision Tree Algorithms with Multi-edited Nearest Neighbor Rule (PAKDD 2003)**\n  - Chenzhou Ye, Jie Yang, Lixiu Yao, Nian-yi Chen\n  - [[Paper]](https://www.researchgate.net/publication/220895462_Improving_Performance_of_Decision_Tree_Algorithms_with_Multi-edited_Nearest_Neighbor_Rule)\n\n- **Arbogodai: a New Approach for Decision Trees (PKDD 2003)**\n  - Djamel A. Zighed, Gilbert Ritschard, Walid Erray, Vasile-Marian Scuturici\n  - [[Paper]](http://mephisto.unige.ch/pub/publications/gr/zig_rit_arbo_pkdd03.pdf)\n\n- **Communication and Memory Efficient Parallel Decision Tree Construction (SDM 2003)**\n  - Ruoming Jin, Gagan Agrawal\n  - [[Paper]](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.4.3059\u0026rep=rep1\u0026type=pdf)\n\n- **Decision Tree Classification of Spatial Data Patterns from Videokeratography using Zernicke Polynomials (SDM 2003)**\n  - Michael D. Twa, Srinivasan Parthasarathy, Thomas W. Raasch, Mark Bullimore\n  - [[Paper]](https://www.researchgate.net/publication/220907147_Decision_Tree_Classification_of_Spatial_Data_Patterns_From_Videokeratography_Using_Zernike_Polynomials)\n\n## 2002\n\n- **Multiclass Alternating Decision Trees (ECML 2002)**\n  - Geoffrey Holmes, Bernhard Pfahringer, Richard Kirkby, Eibe Frank, Mark A. Hall\n  - [[Paper]](https://www.cs.waikato.ac.nz/~bernhard/papers/ecml2002.pdf)\n  \n- **Heterogeneous Forests of Decision Trees (ICANN 2002)**\n  - Krzysztof Grabczewski, Wlodzislaw Duch\n  - [[Paper]](https://fizyka.umk.pl/publications/kmk/02forest.pdf)\n\n- **Solving the Fragmentation Problem of Decision Trees by Discovering Boundary Emerging Patterns (ICDM 2002)**\n  - Jinyan Li, Limsoon Wong\n  - [[Paper]](https://ieeexplore.ieee.org/document/1184021)\n\n- **Solving the Fragmentation Problem of Decision Trees by Discovering Boundary Emerging Patterns (ICDM 2002)**\n  - Jinyan Li, Limsoon Wong\n  - [[Paper]](https://www.comp.nus.edu.sg/~wongls/psZ/decisionTreeandEP-2.ps)\n\n- **Learning Decision Trees Using the Area Under the ROC Curve (ICML 2002)**\n  - César Ferri, Peter A. Flach, José Hernández-Orallo\n  - [[Paper]](http://dmip.webs.upv.es/papers/ICML2002.pdf)\n\n- **Finding an Optimal Gain-Ratio Subset-Split Test for a Set-Valued Attribute in Decision Tree Induction (ICML 2002)**\n  - Fumio Takechi, Einoshin Suzuki\n  - [[Paper]](https://www.researchgate.net/publication/221346121_Finding_an_Optimal_Gain-Ratio_Subset-Split_Test_for_a_Set-Valued_Attribute_in_Decision_Tree_Induction)\n\n- **Efficiently Mining Frequent Trees in a Forest (KDD 2002)**\n  - Mohammed Javeed Zaki\n  - [[Paper]](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.160.8511\u0026rep=rep1\u0026type=pdf)\n\n- **SECRET: a Scalable Linear Regression Tree Algorithm (KDD 2002)**\n  - Alin Dobra, Johannes Gehrke\n  - [[Paper]](http://www.cs.cornell.edu/people/dobra/papers/secret-extended.pdf)\n\n- **Instability of Decision Tree Classification Algorithms (KDD 2002)**\n  - Ruey-Hsia Li, Geneva G. Belford\n  - [[Paper]](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.12.8094\u0026rep=rep1\u0026type=pdf)\n\n- **Extracting Decision Trees From Trained Neural Networks (KDD 2002)**\n  - Olcay Boz\n  - [[Paper]](http://dspace.library.iitb.ac.in/jspui/bitstream/10054/1285/1/5664.pdf)\n\n- **Dyadic Classification Trees via Structural Risk Minimization (NIPS 2002)**\n  - Clayton D. Scott, Robert D. Nowak\n  - [[Paper]](https://papers.nips.cc/paper/2198-dyadic-classification-trees-via-structural-risk-minimization.pdf)\n  \n- **Approximate Splitting for Ensembles of Trees using Histograms (SDM 2002)**\n  - Chandrika Kamath, Erick Cantú-Paz, David Littau\n  - [[Paper]](https://pdfs.semanticscholar.org/0855/0a94993a268e4e3e99c41e7e0ee43eabd993.pdf)\n\n## 2001\n- **Japanese Named Entity Recognition based on a Simple Rule Generator and Decision Tree Learning (ACL 2001)**\n  - Hideki Isozaki\n  - [[Paper]](https://www.aclweb.org/anthology/P01-1041)\n\n- **Message Length as an Effective Ockham's Razor in Decision Tree Induction (AISTATS 2001)**\n  - Scott Needham, David L. Dowe\n  - [[Paper]](www.gatsby.ucl.ac.uk/aistats/aistats2001/files/needham122.ps)\n\n- **SQL Database Primitives for Decision Tree Classifiers (CIKM 2001)**\n  - Kai-Uwe Sattler, Oliver Dunemann\n  - [[Paper]](http://fusion.cs.uni-magdeburg.de/pubs/classprim.pdf)\n  \n- **A Unified Framework for Evaluation Metrics in Classification Using Decision Trees (ECML 2001)**\n  - Ricardo Vilalta, Mark Brodie, Daniel Oblinger, Irina Rish\n  - [[Paper]](https://scholar.harvard.edu/files/nkc/files/2015_framework_for_benefit_risk_assessment_value_in_health.pdf)\n\n- **Backpropagation in Decision Trees for Regression (ECML 2001)**\n  - Victor Medina-Chico, Alberto Suárez, James F. Lutsko\n  - [[Paper]](https://link.springer.com/chapter/10.1007/3-540-44795-4_30)\n\n- **Consensus Decision Trees: Using Consensus Hierarchical Clustering for Data Relabelling and Reduction (ECML 2001)**\n  - Branko Kavsek, Nada Lavrac, Anuska Ferligoj\n  - [[Paper]](https://link.springer.com/content/pdf/10.1007/3-540-44795-4_22.pdf)\n\n- **Mining Decision Trees from Data Streams in a Mobile Environment (ICDM 2001)**\n  - Hillol Kargupta, Byung-Hoon Park\n  - [[Paper]](https://ieeexplore.ieee.org/document/989530)\n\n- **Efficient Determination of Dynamic Split Points in a Decision Tree (ICDM 2001)**\n  - David Maxwell Chickering, Christopher Meek, Robert Rounthwaite\n  - [[Paper]](https://pdfs.semanticscholar.org/3587/a245c34ea415b205a903bde3220eb533d1a7.pdf)\n\n- **A Comparison of Stacking with Meta Decision Trees to Bagging, Boosting, and Stacking with other Methods (ICDM 2001)**\n  - Bernard Zenko, Ljupco Todorovski, Saso Dzeroski\n  - [[Paper]](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.23.3118\u0026rep=rep1\u0026type=pdf)\n\n- **Efficient Algorithms for Decision Tree Cross-Validation (ICML 2001)**\n  - Hendrik Blockeel, Jan Struyf\n  - [[Paper]](http://www.jmlr.org/papers/volume3/blockeel02a/blockeel02a.pdf)\n\n- **Bias Correction in Classification Tree Construction (ICML 2001)**\n  - Alin Dobra, Johannes Gehrke\n  - [[Paper]](http://www.cs.cornell.edu/people/dobra/papers/icml2001-bias.pdf)\n\n- **Breeding Decision Trees Using Evolutionary Techniques (ICML 2001)**\n  - Athanassios Papagelis, Dimitrios Kalles\n  - [[Paper]](http://www.gatree.com/data/BreedinDecisioTreeUsinEvo.pdf)\n\n- **Obtaining Calibrated Probability Estimates from Decision Trees and Naive Bayesian Classifiers (ICML 2001)**\n  - Bianca Zadrozny, Charles Elkan\n  - [[Paper]](http://cseweb.ucsd.edu/~elkan/calibrated.pdf)\n\n- **Temporal Decision Trees or the lazy ECU vindicated (IJCAI 2001)**\n  - Luca Console, Claudia Picardi, Daniele Theseider Dupré\n  - [[Paper]](https://www.researchgate.net/publication/220815333_Temporal_Decision_Trees_or_the_lazy_ECU_vindicated)\n  \n- **Data Mining Criteria for Tree-based Regression and Classification (KDD 2001)**\n  - Andreas Buja, Yung-Seop Lee\n  - [[Paper]](https://repository.upenn.edu/cgi/viewcontent.cgi?referer=https://www.google.com/\u0026httpsredir=1\u0026article=1406\u0026context=statistics_papers)\n\n- **A Decision Tree of Bigrams is an Accurate Predictor of Word Sense (NAACL 2001)**\n  - Ted Pedersen\n  - [[Paper]](https://www.aclweb.org/anthology/N01-1011)\n  \n- **Rule Reduction over Numerical Attributes in Decision Tree Using Multilayer Perceptron (PAKDD 2001)**\n  - DaeEun Kim, Jaeho Lee\n  - [[Paper]](https://dl.acm.org/citation.cfm?id=693490)\n\n- **A Scalable Algorithm for Rule Post-pruning of Large Decision Trees (PAKDD 2001)**\n  - Trong Dung Nguyen, Tu Bao Ho, Hiroshi Shimodaira\n  - [[Paper]](https://link.springer.com/chapter/10.1007/3-540-45357-1_49)\n\n- **Optimizing the Induction of Alternating Decision Trees (PAKDD 2001)**\n  - Bernhard Pfahringer, Geoffrey Holmes, Richard Kirkby\n  - [[Paper]](https://www.researchgate.net/publication/33051701_Optimizing_the_Induction_of_Alternating_Decision_Trees)\n\n- **Interactive Construction of Decision Trees (PAKDD 2001)**\n  - Jianchao Han, Nick Cercone\n  - [[Paper]](https://pure.tue.nl/ws/files/3522084/672434611234867.pdf)\n\n- **Bloomy Decision Tree for Multi-objective Classification (PKDD 2001)**\n  - Einoshin Suzuki, Masafumi Gotoh, Yuta Choki\n  - [[Paper]](https://link.springer.com/chapter/10.1007/3-540-44794-6_36)\n  \n- **A Fourier Analysis Based Approach to Learning Decision Trees in a Distributed Environment (SDM 2001)**\n  - Byung-Hoon Park, Rajeev Ayyagari, Hillol Kargupta\n  - [[Paper]](https://archive.siam.org/meetings/sdm01/pdf/sdm01_19.pdf)\n  \n## 2000\n\n- **Intuitive Representation of Decision Trees Using General Rules and Exceptions (AAAI 2000)**\n  - Bing Liu, Minqing Hu, Wynne Hsu\n  - [[Paper]](https://pdfs.semanticscholar.org/e284/96551e595f1850a53f93affa98919147712f.pdf)\n\n- **Tagging Unknown Proper Names Using Decision Trees (ACL 2000)**\n  - Frédéric Béchet, Alexis Nasr, Franck Genet\n  - [[Paper]](https://www.aclweb.org/anthology/P00-1011)\n\n- **Clustering Through Decision Tree Construction (CIKM 2000)**\n  - Bing Liu, Yiyuan Xia, Philip S. Yu\n  - [[Paper]](https://dl.acm.org/citation.cfm?id=354775)\n\n- **Handling Continuous-Valued Attributes in Decision Tree with Neural Network Modelling (ECML 2000)**\n  - DaeEun Kim, Jaeho Lee\n  - [[Paper]](https://link.springer.com/content/pdf/10.1007/3-540-45164-1_22.pdf)\n\n- **Investigation and Reduction of Discretization Variance in Decision Tree Induction (ECML 2000)**\n  - Pierre Geurts, Louis Wehenkel\n  - [[Paper]](https://link.springer.com/chapter/10.1007/3-540-45164-1_17)\n\n- **Nonparametric Regularization of Decision Trees (ECML 2000)**\n  - Tobias Scheffer\n  - [[Paper]](https://link.springer.com/chapter/10.1007/3-540-45164-1_36)\n\n- **Exploiting the Cost (In)sensitivity of Decision Tree Splitting Criteria (ICML 2000)**\n  - Chris Drummond, Robert C. Holte\n  - [[Paper]](https://pdfs.semanticscholar.org/160e/21c3acc925b60dc040cb1705e58bb166b045.pdf)\n\n- **Multi-agent Q-learning and Regression Trees for Automated Pricing Decisions (ICML 2000)**\n  - Manu Sridharan, Gerald Tesauro\n  - [[Paper]](https://manu.sridharan.net/files/icml00.pdf)\n\n- **Growing Decision Trees on Support-less Association Rules (KDD 2000)**\n  - Ke Wang, Senqiang Zhou, Yu He\n  - [[Paper]](https://www2.cs.sfu.ca/~wangk/pub/kdd002.pdf)\n\n- **Efficient Algorithms for Constructing Decision Trees with Constraints (KDD 2000)**\n  - Minos N. Garofalakis, Dongjoon Hyun, Rajeev Rastogi, Kyuseok Shim\n  - [[Paper]](http://www.softnet.tuc.gr/~minos/Papers/kdd00-cam.pdf)\n\n- **Interactive Visualization in Mining Large Decision Trees (PAKDD 2000)**\n  - Trong Dung Nguyen, Tu Bao Ho, Hiroshi Shimodaira\n  - [[Paper]](https://link.springer.com/content/pdf/10.1007/3-540-45571-X_40.pdf)\n\n- **VQTree: Vector Quantization for Decision Tree Induction (PAKDD 2000)**\n  - Shlomo Geva, Lawrence Buckingham\n  - [[Paper]](https://link.springer.com/chapter/10.1007%2F3-540-45571-X_41)\n\n- **Some Enhencements of Decision Tree Bagging (PKDD 2000)**\n  - Pierre Geurts\n  - [[Paper]](https://link.springer.com/chapter/10.1007/3-540-45372-5_14)\n\n- **Combining Multiple Models with Meta Decision Trees (PKDD 2000)**\n  - Ljupco Todorovski, Saso Dzeroski\n  - [[Paper]](http://kt.ijs.si/bernard/mdts/pub01.pdf)\n\n- **Induction of Multivariate Decision Trees by Using Dipolar Criteria (PKDD 2000)**\n  - Leon Bobrowski, Marek Kretowski\n  - [[Paper]](https://link.springer.com/chapter/10.1007/3-540-45372-5_33)\n\n- **Decision Tree Toolkit: A Component-Based Library of Decision Tree Algorithms (PKDD 2000)**\n  - Nikos Drossos, Athanassios Papagelis, Dimitrios Kalles\n  - [[Paper]](https://link.springer.com/chapter/10.1007/3-540-45372-5_40)\n\n## 1999\n- **Modeling Decision Tree Performance with the Power Law (AISTATS 1999)**\n  - Lewis J. Frey, Douglas H. Fisher\n  - [[Paper]](https://www.microsoft.com/en-us/research/wp-content/uploads/2017/01/ModelingTree.pdf)\n\n- **Causal Mechanisms and Classification Trees for Predicting Chemical Carcinogens (AISTATS 1999)**\n  - Louis Anthony Cox Jr.\n  - [[Paper]](https://pdfs.semanticscholar.org/0d7b/1d55c5abfd024aacf645c66d0c90c283814e.pdf)\n\n- **POS Tags and Decision Trees for Language Modeling (EMNLP 1999)**\n  - Peter A. Heeman\n  - [[Paper]](https://www.aclweb.org/anthology/W99-0617)\n\n- **Lazy Bayesian Rules: A Lazy Semi-Naive Bayesian Learning Technique Competitive to Boosting Decision Trees (ICML 1999)**\n  - Zijian Zheng, Geoffrey I. Webb, Kai Ming Ting\n  - [[Paper]](https://pdfs.semanticscholar.org/067e/86836ddbcb5e2844e955c16e058366a18c77.pdf)\n\n- **The Alternating Decision Tree Learning Algorithm (ICML 1999)**\n  - Yoav Freund, Llew Mason\n  - [[Paper]](https://cseweb.ucsd.edu/~yfreund/papers/atrees.pdf)\n  - [[Code]](https://github.com/rajanil/mkboost)\n\n- **Boosting with Multi-Way Branching in Decision Trees (NIPS 1999)**\n  - Yishay Mansour, David A. McAllester\n  - [[Paper]](https://papers.nips.cc/paper/1659-boosting-with-multi-way-branching-in-decision-trees.pdf)\n\n## 1998\n- **Learning Sorting and Decision Trees with POMDPs (ICML 1998)**\n  - Blai Bonet, Hector Geffner\n  - [[Paper]](https://bonetblai.github.io/reports/icml98-learning.pdf)\n\n- **Using a Permutation Test for Attribute Selection in Decision Trees (ICML 1998)**\n  - Eibe Frank, Ian H. Witten\n  - [[Paper]](https://pdfs.semanticscholar.org/9aa9/21b0203e06e98b49bf726a33e124f4310ea3.pdf)\n\n- **A Fast and Bottom-Up Decision Tree Pruning Algorithm with Near-Optimal Generalization (ICML 1998)**\n  - Michael J. Kearns, Yishay Mansour\n  - [[Paper]](https://www.cis.upenn.edu/~mkearns/papers/pruning.pdf)\n\n## 1997\n- **Pessimistic Decision Tree Pruning Based Continuous-Time (ICML 1997)**\n  - Yishay Mansour\n  - [[Paper]](https://pdfs.semanticscholar.org/b6fc/e37612db10a9756b904b5e79e1144ca12574.pdf)\n\n- **PAC Learning with Constant-Partition Classification Noise and Applications to Decision Tree Induction (ICML 1997)**\n  - Scott E. Decatur\n  - [[Paper]](https://www.semanticscholar.org/paper/PAC-Learning-with-Constant-Partition-Classification-Decatur/dd205073aeb512ecd1e823b35f556058fdeea5e0)\n\n- **Option Decision Trees with Majority Votes (ICML 1997)**\n  - Ron Kohavi, Clayton Kunz\n  - [[Paper]](https://pdfs.semanticscholar.org/383b/381d1ac0bb41ec595e0d1603ed642809eb86.pdf)\n\n- **Integrating Feature Construction with Multiple Classifiers in Decision Tree Induction (ICML 1997)**\n  - Ricardo Vilalta, Larry A. Rendell\n  - [[Paper]](https://pdfs.semanticscholar.org/1f73/d9d409a75d16871cfa1182ac72b37c839d86.pdf)\n\n- **Functional Models for Regression Tree Leaves (ICML 1997)**\n  - Luís Torgo\n  - [[Paper]](https://pdfs.semanticscholar.org/48e4/b3187ca234308e97e1ac0cab84222c603bdd.pdf)\n\n- **The Effects of Training Set Size on Decision Tree Complexity (ICML 1997)**\n  - Tim Oates, David D. Jensen\n  - [[Paper]](https://pdfs.semanticscholar.org/e003/9dbdec3bd4cfbb3273b623fbed2d6b2f0cc9.pdf)\n\n- **Unsupervised On-line Learning of Decision Trees for Hierarchical Data Analysis (NIPS 1997)**\n  - Marcus Held, Joachim M. Buhmann\n  - [[Paper]](https://papers.nips.cc/paper/1479-unsupervised-on-line-learning-of-decision-trees-for-hierarchical-data-analysis.pdf)\n\n- **Data-Dependent Structural Risk Minimization for Perceptron Decision Trees (NIPS 1997)**\n  - John Shawe-Taylor, Nello Cristianini\n  - [[Paper]](https://papers.nips.cc/paper/1359-data-dependent-structural-risk-minimization-for-perceptron-decision-trees)\n\n- **Generalization in Decision Trees and DNF: Does Size Matter (NIPS 1997)**\n  - Mostefa Golea, Peter L. Bartlett, Wee Sun Lee, Llew Mason\n  - [[Paper]](https://papers.nips.cc/paper/1340-generalization-in-decision-trees-and-dnf-does-size-matter.pdf)\n\n## 1996\n- **Second Tier for Decision Trees (ICML 1996)**\n  - Miroslav Kubat\n  - [[Paper]](https://pdfs.semanticscholar.org/b619/7c531b1c83dfaa52563449f9b8248cc68c5a.pdf)\n\n- **Non-Linear Decision Trees - NDT (ICML 1996)**\n  - Andreas Ittner, Michael Schlosser\n  - [[Paper]](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.85.2133\u0026rep=rep1\u0026type=pdf)\n\n- **Learning Relational Concepts with Decision Trees (ICML 1996)**\n  - Peter Geibel, Fritz Wysotzki\n  - [[Paper]](https://pdfs.semanticscholar.org/32f1/78d7266fee779257b87ac8f948951db57d1e.pdf)\n\n## 1995\n- **A Hill-Climbing Approach for Optimizing Classification Trees (AISTATS 1995)**\n  - Xiaorong Sun, Steve Y. Chiu, Louis Anthony Cox Jr.\n  - [[Paper]](https://link.springer.com/chapter/10.1007%2F978-1-4612-2404-4_11)\n\n- **An Exact Probability Metric for Decision Tree Splitting (AISTATS 1995)**\n  - J. Kent Martin\n  - [[Paper]](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.48.6378\u0026rep=rep1\u0026type=pdf)\n\n- **On Pruning and Averaging Decision Trees (ICML 1995)**\n  - Jonathan J. Oliver, David J. Hand\n  - [[Paper]](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.53.6733\u0026rep=rep1\u0026type=pdf)\n\n- **On Handling Tree-Structured Attributed in Decision Tree Learning (ICML 1995)**\n  - Hussein Almuallim, Yasuhiro Akiba, Shigeo Kaneda\n  - [[Paper]](https://www.sciencedirect.com/science/article/pii/B9781558603776500116)\n\n- **Retrofitting Decision Tree Classifiers Using Kernel Density Estimation (ICML 1995)**\n  - Padhraic Smyth, Alexander G. Gray, Usama M. Fayyad\n  - [[Paper]](https://pdfs.semanticscholar.org/3a05/8ab505f096b23962591bb14e495a543aa2a1.pdf)\n\n- **Increasing the Performance and Consistency of Classification Trees by Using the Accuracy Criterion at the Leaves (ICML 1995)**\n  - David J. Lubinsky\n  - [[Paper]](https://www.sciencedirect.com/science/article/pii/B9781558603776500530)\n\n- **Efficient Algorithms for Finding Multi-way Splits for Decision Trees (ICML 1995)**\n  - Truxton Fulton, Simon Kasif, Steven Salzberg\n  - [[Paper]](https://www.sciencedirect.com/science/article/pii/B9781558603776500384)\n\n- **Theory and Applications of Agnostic PAC-Learning with Small Decision Trees (ICML 1995)**\n  - Peter Auer, Robert C. Holte, Wolfgang Maass\n  - [[Paper]](https://igi-web.tugraz.at/PDF/77.pdf)\n\n- **Boosting Decision Trees (NIPS 1995)**\n  - Harris Drucker, Corinna Cortes\n  - [[Paper]](http://papers.nips.cc/paper/1059-boosting-decision-trees.pdf)\n\n- **Using Pairs of Data-Points to Define Splits for Decision Trees (NIPS 1995)**\n  - Geoffrey E. Hinton, Michael Revow\n  - [[Paper]](https://www.cs.toronto.edu/~hinton/absps/bcart.pdf)\n\n- **A New Pruning Method for Solving Decision Trees and Game Trees (UAI 1995)**\n  - Prakash P. Shenoy\n  - [[Paper]](https://arxiv.org/abs/1302.4981)\n\n## 1994\n- **A Statistical Approach to Decision Tree Modeling (ICML 1994)**\n  - Michael I. Jordan\n  - [[Paper]](https://www.sciencedirect.com/science/article/pii/B9781558603356500519)\n\n- **In Defense of C4.5: Notes Learning One-Level Decision Trees (ICML 1994)**\n  - Tapio Elomaa\n  - [[Paper]](http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.30.9386)\n\n- **An Improved Algorithm for Incremental Induction of Decision Trees (ICML 1994)**\n  - Paul E. Utgoff\n  - [[Paper]](https://www.sciencedirect.com/science/article/pii/B9781558603356500465)\n  \n- **Decision Tree Parsing using a Hidden Derivation Model (NAACL 1994)**\n  - Frederick Jelinek, John D. Lafferty, David M. Magerman, Robert L. Mercer, Adwait Ratnaparkhi, Salim Roukos\n  - [[Paper]](http://acl-arc.comp.nus.edu.sg/archives/acl-arc-090501d3/data/pdf/anthology-PDF/H/H94/H94-1052.pdf)\n\n## 1993\n- **Using Decision Trees to Improve Case-Based Learning (ICML 1993)**\n  - Claire Cardie\n  - [[Paper]](https://www.cs.cornell.edu/home/cardie/papers/ml-93.ps)\n  \n## 1991\n- **Context Dependent Modeling of Phones in Continuous Speech Using Decision Trees (NAACL 1991)**\n  - Lalit R. Bahl, Peter V. de Souza, P. S. Gopalakrishnan, David Nahamoo, Michael Picheny\n  - [[Paper]](https://www.aclweb.org/anthology/H91-1051.pdf)\n\n## 1989\n- **Performance Comparisons Between Backpropagation Networks and Classification Trees on Three Real-World Applications (NIPS 1989)**\n  - Les E. Atlas, Ronald A. Cole, Jerome T. Connor, Mohamed A. El-Sharkawi, Robert J. Marks II, Yeshwant K. Muthusamy, Etienne Barnard\n  - [[Paper]](https://papers.nips.cc/paper/203-performance-comparisons-between-backpropagation-networks-and-classification-trees-on-three-real-world-applications)\n\n## 1988\n- **Multiple Decision Trees (UAI 1988)**\n  - Suk Wah Kwok, Chris Carter\n  - [[Paper]](https://arxiv.org/abs/1304.2363)\n\n## 1987\n- **Decision Tree Induction Systems: A Bayesian Analysis (UAI 1987)**\n  - Wray L. Buntine\n  - [[Paper]](https://arxiv.org/abs/1304.2732)\n  \n-----------------------------------------------------------------------\n\n**License**\n\n- [CC0 Universal](https://github.com/benedekrozemberczki/awesome-decision-tree-papers/blob/master/LICENSE)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbenedekrozemberczki%2Fawesome-decision-tree-papers","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbenedekrozemberczki%2Fawesome-decision-tree-papers","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbenedekrozemberczki%2Fawesome-decision-tree-papers/lists"}