Fairness

Minimum Robust Multi-Submodular Cover for Fairness AAAI 2021 MIN_PT: An European Portuguese Lexicon for Minorities Related Terms ACL 2021 Mitigating Biases in Toxic Language Detection through Invariant Rationalization ACL 2021 Mitigating Bias in Session-based Cyberbullying Detection: A Non-Compromising Approach ACL 2021 Mitigating Face Recognition Bias via Group Adaptive Classifier CVPR 2021 Mitigating Language-Dependent Ethnic Bias in BERT EMNLP 2021 Mitigating Political Bias in Language Models through Reinforced Calibration AAAI 2021 Mitigation of Diachronic Bias in Fake News Detection Dataset EMNLP 2021 Model-based metrics: Sample-efficient estimates of predictive model subpopulation performance MLHC 2021 Modeling Users and Online Communities for Abuse Detection: A Position on Ethics and Explainability EMNLP 2021 Moment Multicalibration for Uncertainty Estimation COLT 2021 Multi-group Agnostic PAC Learnability ICML 2021 Multi-Objective SPIBB: Seldonian Offline Policy Improvement with Safety Constraints in Finite MDPs NeurIPS 2021 Oblivious Data for Fairness with Kernels JMLR 2021 On Disentangled Representations Learned from Correlated Data ICML 2021 On Dyadic Fairness: Exploring and Mitigating Bias in Graph Connections ICLR 2021 One Explanation is Not Enough: Structured Attention Graphs for Image Classification NeurIPS 2021 On Fair Division under Heterogeneous Matroid Constraints AAAI 2021 On learning and representing social meaning in NLP: a sociolinguistic perspective NAACL 2021 On Learning Deep Models with Imbalanced Data Distribution AAAI 2021 On Releasing Annotator-Level Labels and Information in Datasets EMNLP 2021 On the Impact of Random Seeds on the Fairness of Clinical Classifiers NAACL 2021 On the Privacy Properties of GAN-generated Samples AISTATS 2021 On the Problem of Underranking in Group-Fair Ranking ICML 2021 On the PTAS for Maximin Shares in an Indivisible Mixed Manna AAAI 2021