Fairness

Learning Not to Learn: Training Deep Neural Networks With Biased Data CVPR 2019 Learning Optimal and Fair Decision Trees for Non-Discriminative Decision-Making AAAI 2019 Learning Optimal Fair Policies ICML 2019 Learning to Address Health Inequality in the United States with a Bayesian Decision Network AAAI 2019 Leveraging Labeled and Unlabeled Data for Consistent Fair Binary Classification NeurIPS 2019 Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Them NAACL 2019 Making Decisions that Reduce Discriminatory Impacts ICML 2019 Many Faces of Feature Importance: Comparing Built-in and Post-hoc Feature Importance in Text Classification EMNLP 2019 Matroid Constrained Fair Allocation Problem AAAI 2019 Matroids, Matchings, and Fairness AISTATS 2019 Maximin-Aware Allocations of Indivisible Goods IJCAI 2019 mdfa: Multi-Differential Fairness Auditor for Black Box Classifiers IJCAI 2019 Measuring Bias in Contextualized Word Representations ACL 2019 Measuring Gender Bias in Word Embeddings across Domains and Discovering New Gender Bias Word Categories ACL 2019 Mitigating Gender and L1 Differences to Improve State and Trait Recognition Interspeech 2019 Mitigating Gender Bias in Natural Language Processing: Literature Review ACL 2019 Multi-Criteria Dimensionality Reduction with Applications to Fairness NeurIPS 2019 Near Neighbor: Who is the Fairest of Them All? NeurIPS 2019 Noise-tolerant fair classification NeurIPS 2019 Obtaining Fairness using Optimal Transport Theory ICML 2019 Offline Contextual Bandits with High Probability Fairness Guarantees NeurIPS 2019 One-Network Adversarial Fairness AAAI 2019 On Fair Cost Sharing Games in Machine Learning AAAI 2019 On Human-Aligned Risk Minimization NeurIPS 2019 On Making Reading Comprehension More Comprehensive EMNLP 2019