Fairness Reading Group

The Fairness Reading Group meets every Wednesday at 2:30-3:30pm, usually in CS 4310. Details will be announced via the mailing list. Below we maintain an archive of past presentations.
Date Title Speaker
11/15/2017 Interpreting Classifiers through Attribute Interactions in Datasets Samuel Drews
11/01/2017 A Convex Framework for Fair Regression Yifeng Teng
10/25/2017 On Fairness and Calibration David Merrell
10/18/2017 Decoupled classifiers for fair and efficient machine learning Xuezhou Zhang
10/11/2017 Counterfactual Fairness Group Discussion
10/04/2017 Avoiding Discrimination through Causal Reasoning Group Discussion
09/27/2017 Algorithmic Transparency via Quantitative Input Influence Samuel Drews
09/20/2017 Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings Yingyu Liang
08/23/2017 Proxy Discrimination in Data-Driven Systems Aws Albarghouthi
08/16/2017 Algorithmic decision making and the cost of fairness Yifeng Teng
08/09/2017 Fairness in Reinforcement Learning David Merrell
08/02/2017 Equality of Opportunity in Supervised Learning Xuezhou Zhang