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awesome-long-tail-learning
https://github.com/Stomach-ache/awesome-long-tail-learning
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Binary Relevance
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Slice: Scalable linear extreme classifiers trained on 100 million labels for related searches
- PD-Sparse: A Primal and Dual Sparse Approach to Extreme Multiclass and Multilabel Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
- Data Scarcity, Robustness and Extreme Multi-label Classification
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Tree-based Methods
- Extreme Multi-label Learning for Semantic Matching in Product Search
- Probabilistic Label Trees for Extreme Multi-label Classification
- Online probabilistic label trees
- LdSM: Logarithm-depth Streaming Multi-label Decision Trees
- Bonsai - Diverse and Shallow Trees for Extreme Multi-label Classification
- CRAFTML, an Efficient Clustering-based Random Forest for Extreme Multi-label Learning
- Parabel: Partitioned Label Trees for Extreme Classification with Application to Dynamic Search Advertising
- Extreme F-Measure Maximization using Sparse Probability Estimates
- Extreme Multi-label Loss Functions for Recommendation, Tagging, Ranking & Other Missing Label Applications
- A Fast, Accurate and Stable Tree-classifier for eXtreme Multi-label Learning
- Label Partitioning For Sublinear Ranking
- Multi-Label Learning with Millions of Labels: Recommending Advertiser Bid Phrases for Web Pages
- Efficient label tree learning for large scale object recognition - class |
- Label embedding trees for large multi-class tasks - class |
- Effective and Efficient Multilabel Classification in Domains with Large Number of Labels
- Extreme Multi-label Learning for Semantic Matching in Product Search
- Probabilistic Label Trees for Extreme Multi-label Classification
- Online probabilistic label trees
- LdSM: Logarithm-depth Streaming Multi-label Decision Trees
- Bonsai - Diverse and Shallow Trees for Extreme Multi-label Classification
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Embedding-based Methods
- Distributional Semantics Meets Multi-Label Learning - trier.de/rec/bibtex/conf/aaai/0001WNK0R19)|
- Ranking-Based Autoencoder for Extreme Multi-label Classification
- Breaking the Glass Ceiling for Embedding-Based Classifiers for Large Ouput Spaces
- Sparse Local Embeddings for Extreme Multi-label Classification
- Ranking-Based Autoencoder for Extreme Multi-label Classification
- AnnexML: Approximate Nearest Neighbor Search for Extreme Multi-label Classification
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Speed-up and Compression
- SOLAR: Sparse Orthogonal Learned and Random Embeddings
- EXTREME CLASSIFICATION VIA ADVERSARIAL SOFTMAX APPROXIMATION
- Stochastic Negative Mining for Learning with Large Output Spaces
- Extreme Classification in Log Memory using Count-Min Sketch: A Case Study of Amazon Search with 50M Products - trier.de/rec/bibtex/journals/corr/abs-1910-13830) |
- An Embarrassingly Simple Baseline for eXtreme Multi-label Prediction
- Accelerating Extreme Classification via Adaptive Feature Agglomeration - trier.de/rec/bibtex/conf/ijcai/JalanK19), authors from IIT |
- Fast Training for Large-Scale One-versus-All Linear Classifiers using Tree-Structured Initialization - trier.de/rec/bibtex/conf/sdm/FangCHF19) |
- SOLAR: Sparse Orthogonal Learned and Random Embeddings
- EXTREME CLASSIFICATION VIA ADVERSARIAL SOFTMAX APPROXIMATION
- An Embarrassingly Simple Baseline for eXtreme Multi-label Prediction
- Accelerating Extreme Classification via Adaptive Feature Agglomeration - trier.de/rec/bibtex/conf/ijcai/JalanK19), authors from IIT |
- Large-Scale Training System for 100-Million Classification at Alibaba
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Noval XML Settings
- Extreme Multi-label Classification from Aggregated Labels - instance learning in XML |
- Unbiased Loss Functions for Extreme Classification With Missing Labels
- Deep Streaming Label Learning - label learning |
- Streaming Label Learning for Modeling Labels on the Fly - label learning |
- Streaming Label Learning for Modeling Labels on the Fly - label learning |
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Theoretical Studies
- Sparse Extreme Multi-label Learning with Oracle Property
- Multilabel reductions: what is my loss optimising? - yIu3FslYJ:scholar.google.com/&output=citation&scisdr=CgUK3ErIELLQ673T7yk:AAGBfm0AAAAAX2LW9ylvLsuvrfJKgZu4PETv4cbbc6GX&scisig=AAGBfm0AAAAAX2LW94UGV94llU318HCTU_i63fA5l1Yw&scisf=4&ct=citation&cd=-1&hl=en), by Google |
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Text Classification
- BGNN-XML: Bilateral Graph Neural Networks for Extreme Multi-label Text Classification
- SiameseXML: Siamese Networks meet Extreme Classifiers with 100M Labels
- GNN-XML: Graph Neural Networks for Extreme Multi-label Text Classification
- Pretrained Generalized Autoregressive Model with Adaptive Probabilistic Label Clusters for Extreme Multi-label Text Classification
- Large-Scale Multi-Label Text Classification on EU Legislation - Lex 4.3K, [bibtex](https://dblp.uni-trier.de/rec/bibtex/conf/acl/ChalkidisFMA19) |
- X-BERT: eXtreme Multi-label Text Classification with BERT - BERT) by [Yiming Yang](https://scholar.google.com/citations?hl=en&user=MlZq4XwAAAAJ&view_op=list_works&sortby=pubdate), Inderjit Dhillon |
- Few-Shot and Zero-Shot Multi-Label Learning for Structured Label Spaces - shot, zero-shot, evaluation metric |
- Deep Learning for Extreme Multi-label Text Classification - trier.de/rec/bibtex0/conf/sigir/LiuCWY17)|
- BGNN-XML: Bilateral Graph Neural Networks for Extreme Multi-label Text Classification
- BGNN-XML: Bilateral Graph Neural Networks for Extreme Multi-label Text Classification
- BGNN-XML: Bilateral Graph Neural Networks for Extreme Multi-label Text Classification
- BGNN-XML: Bilateral Graph Neural Networks for Extreme Multi-label Text Classification
- BGNN-XML: Bilateral Graph Neural Networks for Extreme Multi-label Text Classification
- BGNN-XML: Bilateral Graph Neural Networks for Extreme Multi-label Text Classification
- BGNN-XML: Bilateral Graph Neural Networks for Extreme Multi-label Text Classification
- BGNN-XML: Bilateral Graph Neural Networks for Extreme Multi-label Text Classification
- BGNN-XML: Bilateral Graph Neural Networks for Extreme Multi-label Text Classification
- BGNN-XML: Bilateral Graph Neural Networks for Extreme Multi-label Text Classification
- BGNN-XML: Bilateral Graph Neural Networks for Extreme Multi-label Text Classification
- X-BERT: eXtreme Multi-label Text Classification with BERT - BERT) by [Yiming Yang](https://scholar.google.com/citations?hl=en&user=MlZq4XwAAAAJ&view_op=list_works&sortby=pubdate), Inderjit Dhillon |
- AttentionXML: Extreme Multi-Label Text Classification with Multi-Label Attention Based Recurrent Neural Networks
- AttentionXML: Extreme Multi-Label Text Classification with Multi-Label Attention Based Recurrent Neural Networks
- GNN-XML: Graph Neural Networks for Extreme Multi-label Text Classification
- Correlation Networks for Extreme Multi-label Text Classification
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Others
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Label Correlation
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Long-tailed Continual Learning
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Train/Test Split
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XML Seminar
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Survey References:
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Categories