Fairness

Data preprocessing to mitigate bias: A maximum entropy based approach ICML 2020 DeBayes: a Bayesian Method for Debiasing Network Embeddings ICML 2020 Deep Fair Clustering for Visual Learning CVPR 2020 Deep F-Measure Maximization for End-to-End Speech Understanding Interspeech 2020 Demographics Should Not Be the Reason of Toxicity: Mitigating Discrimination in Text Classifications with Instance Weighting ACL 2020 Demoting Racial Bias in Hate Speech Detection ACL 2020 Deontological Ethics By Monotonicity Shape Constraints AISTATS 2020 Dependent randomized rounding for clustering and partition systems with knapsack constraints AISTATS 2020 Designing Committees for Mitigating Biases AAAI 2020 Detecting and understanding moral biases in news ACL 2020 Detecting East Asian Prejudice on Social Media EMNLP 2020 Detecting Independent Pronoun Bias with Partially-Synthetic Data Generation EMNLP 2020 Differentially Private and Fair Classification via Calibrated Functional Mechanism AAAI 2020 Differentially Private Representation for NLP: Formal Guarantee and An Empirical Study on Privacy and Fairness EMNLP 2020 Does Gender Matter? Towards Fairness in Dialogue Systems COLING 2020 Do Face Masks Introduce Bias in Speech Technologies? The Case of Automated Scoring of Speaking Proficiency Interspeech 2020 Don't Judge an Object by Its Context: Learning to Overcome Contextual Bias CVPR 2020 Double-Hard Debias: Tailoring Word Embeddings for Gender Bias Mitigation ACL 2020 Do We Need Zero Training Loss After Achieving Zero Training Error? ICML 2020 Enhancing Bias Detection in Political News Using Pragmatic Presupposition ACL 2020 Enhancing the Identification of Cyberbullying through Participant Roles EMNLP 2020 Ensuring Fairness Beyond the Training Data NeurIPS 2020 Equalized odds postprocessing under imperfect group information AISTATS 2020 Evaluating Bias In Dutch Word Embeddings COLING 2020 Exploiting MMD and Sinkhorn Divergences for Fair and Transferable Representation Learning NeurIPS 2020