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awesome-fairness-in-ai
A curated list of awesome Fairness in AI resources
https://github.com/datamllab/awesome-fairness-in-ai
Last synced: 5 days ago
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Other Fairness Relevant Interpretability Resources
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Mitigation of Representations
- The Mythos of Model Interpretability
- The Mythos of Model Interpretability
- Towards A Rigorous Science of Interpretable Machine Learning
- Techniques for Interpretable Machine Learning
- Methods for Interpreting and Understanding Deep Neural Networks
- Towards A Rigorous Science of Interpretable Machine Learning
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Mitigation of Unfairness
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Mitigation of Machine Learning Models
- Fairness-aware Learning through Regularization Approach
- Fairness-aware Learning through Regularization Approach
- Fairness-aware Learning through Regularization Approach
- Incorporating priors with feature attribution on text classification
- Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations
- Achieving Fairness through Adversarial Learning: an Application to Recidivism Prediction
- Balanced Datasets Are Not Enough: Estimating and Mitigating Gender Bias in Deep Image Representations
- Mitigating Unwanted Biases with Adversarial Learning
- Adversarial Removal of Demographic Attributes from Text Data
- Compositional Fairness Constraints for Graph Embeddings
- Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints
- Mitigating Gender Bias in Captioning Systems
- Women Also Snowboard: Overcoming Bias in Captioning Models
- Learning Credible Deep Neural Networks with Rationale Regularization
- Why Is My Classifier Discriminatory?
- Incorporating Dialectal Variability for Socially Equitable Language Identification
- REPAIR: Removing Representation Bias by Dataset Resampling
- Mitigating Bias in Gender, Age and Ethnicity Classification: a Multi-Task Convolution Neural Network Approach
- InclusiveFaceNet: Improving Face Attribute Detection with Race and Gender Diversity
- Reducing Gender Bias in Abusive Language Detection
- Fairness-aware Learning through Regularization Approach
- Fairness Constraints: Mechanisms for Fair Classification
- Penalizing Unfairness in Binary Classification
- A General Framework for Fair Regression
- Fair Regression: Quantitative Definitions and Reduction-based Algorithms
- Fairness-aware Learning through Regularization Approach
- Fairness-aware Learning through Regularization Approach
- Fairness-aware Learning through Regularization Approach
- Fairness-aware Learning through Regularization Approach
- Fairness-aware Learning through Regularization Approach
- Fairness-aware Learning through Regularization Approach
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Mitigation of Representations
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Review and General Papers
- Fairness in Deep Learning: A Computational Perspective
- The Measure and Mismeasure of Fairness: A Critical Review of Fair Machine Learning
- Fairness and machine learning
- A Survey on Bias and Fairness in Machine Learning
- The Frontiers of Fairness in Machine Learning
- Ensuring fairness in machine learning to advance health equity
- Mitigating Gender Bias in Natural Language Processing: Literature Review
- Fairness in Recommender Systems
- Implementations in Machine Ethics: A Survey
- The Measure and Mismeasure of Fairness: A Critical Review of Fair Machine Learning
- Fairness in Deep Learning: A Computational Perspective
- A Survey on Bias and Fairness in Machine Learning
- The Frontiers of Fairness in Machine Learning
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Measurements of Fairness
- On Formalizing Fairness in Prediction with Machine Learning
- Certifying and removing disparate impact
- Does mitigating ML's impact disparity require treatment disparity?
- Putting Fairness Principles into Practice: Challenges, Metrics, and Improvements
- Beyond Parity: Fairness Objectives for Collaborative Filtering
- 50 Years of Test (Un)fairness: Lessons for Machine Learning
- Fairness Definitions Explained
- Algorithmic Fairness
- Fairness is not Static: Deeper Understanding of Long Term Fairness via Simulation Studies
- Delayed Impact of Fair Machine Learning
- Equality of Opportunity in Supervised Learning
- Bias in data‐driven artificial intelligence systems—An introductory survey
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Demonstration of Bias Phemomenon in Various Applications
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Bias in Machine Learning Models
- Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification
- Deep Learning for Face Recognition: Pride or Prejudiced?
- Examining Gender and Race Bias in Two Hundred Sentiment Analysis Systems
- Demographic Dialectal Variation in Social Media: A Case Study of African-American English
- Feature-Wise Bias Amplification
- ConvNets and ImageNet Beyond Accuracy: Understanding Mistakes and Uncovering Biases
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Bias in Representations
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Fairness Packages and Frameworks
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Conferences
Categories