Fair for All: Best-effort Fairness Guarantees for Classification

no code implementations • 18 Dec 2020 • Anilesh K. Krishnaswamy, Zhihao Jiang, Kangning Wang, Yu Cheng, Kamesh Munagala

Instead, we propose a fairness notion whose guarantee, on each group $g$ in a class $\mathcal{G}$, is relative to the performance of the best classifier on $g$.

Classification Fairness +1

Classification with Strategically Withheld Data

1 code implementation • 18 Dec 2020 • Anilesh K. Krishnaswamy, Haoming Li, David Rein, Hanrui Zhang, Vincent Conitzer

To this end, we present {\sc IC-LR}, a modification of Logistic Regression that removes the incentive to strategically drop features.

Classification General Classification +1

Exploration vs. Exploitation in Team Formation

no code implementations • 18 Sep 2018 • Ramesh Johari, Vijay Kamble, Anilesh K. Krishnaswamy, Hannah Li

An online labor platform faces an online learning problem in matching workers with jobs and using the performance on these jobs to create better future matches.