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Fairness

3337 directly classified papers

Papers per year

Papers

Assessing Disparate Impact of Personalized Interventions: Identifiability and Bounds NIPS 2019
Perturbation Sensitivity Analysis to Detect Unintended Model Biases IJCNLP 2019
The Woman Worked as a Babysitter: On Biases in Language Generation IJCNLP 2019
Are We Modeling the Task or the Annotator? An Investigation of Annotator Bias in Natural Language Understanding Datasets IJCNLP 2019
Fair k-Center Clustering for Data Summarization ICML 2019
Compositional Fairness Constraints for Graph Embeddings ICML 2019
Leveraging Labeled and Unlabeled Data for Consistent Fair Binary Classification NIPS 2019
Noise-tolerant fair classification NIPS 2019
Learning Not to Learn: Training Deep Neural Networks With Biased Data CVPR 2019
Explicit Bias Discovery in Visual Question Answering Models CVPR 2019
Towards Debiasing Fact Verification Models IJCNLP 2019
All Models are Wrong, but Many are Useful: Learning a Variable's Importance by Studying an Entire Class of Prediction Models Simultaneously JMLR 2019
Fairness Constraints: A Flexible Approach for Fair Classification JMLR 2019
Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals JMLR 2019
Scalable Robust Kidney Exchange AAAI 2019
Path-Specific Counterfactual Fairness AAAI 2019
Learning to Address Health Inequality in the United States with a Bayesian Decision Network AAAI 2019
Evaluating Gender Bias in Machine Translation ACL 2019
Investigating Sports Commentator Bias within a Large Corpus of American Football Broadcasts IJCNLP 2019
Convex Formulations for Fair Principal Component Analysis AAAI 2019
Fairness risk measures ICML 2019
Understanding Undesirable Word Embedding Associations ACL 2019
Addressing Age-Related Bias in Sentiment Analysis IJCAI 2019
On the Long-term Impact of Algorithmic Decision Policies: Effort Unfairness and Feature Segregation through Social Learning ICML 2019
Understanding the Origins of Bias in Word Embeddings ICML 2019