Morgenstern, Jamie H

9 publications

NeurIPS 2023 Doubly Constrained Fair Clustering John Dickerson, Seyed Esmaeili, Jamie H Morgenstern, Claire Jie Zhang

NeurIPS 2023 Scalable Membership Inference Attacks via Quantile Regression Martin Bertran, Shuai Tang, Aaron Roth, Michael J. Kearns, Jamie H Morgenstern, Steven Z. Wu

NeurIPS 2022 Active Learning with Safety Constraints Romain Camilleri, Andrew Wagenmaker, Jamie H Morgenstern, Lalit Jain, Kevin G. Jamieson

NeurIPS 2019 Learning Auctions with Robust Incentive Guarantees Jacob D. Abernethy, Rachel Cummings, Bhuvesh Kumar, Sam Taggart, Jamie H Morgenstern

NeurIPS 2019 Multi-Criteria Dimensionality Reduction with Applications to Fairness Uthaipon Tantipongpipat, Samira Samadi, Mohit Singh, Jamie H Morgenstern, Santosh Vempala

NeurIPS 2018 A Smoothed Analysis of the Greedy Algorithm for the Linear Contextual Bandit Problem Sampath Kannan, Jamie H Morgenstern, Aaron Roth, Bo Waggoner, Zhiwei Steven Wu

NeurIPS 2018 The Price of Fair PCA: One Extra Dimension Samira Samadi, Uthaipon Tantipongpipat, Jamie H Morgenstern, Mohit Singh, Santosh Vempala

NeurIPS 2016 Fairness in Learning: Classic and Contextual Bandits Matthew Joseph, Michael Kearns, Jamie H Morgenstern, Aaron Roth

NeurIPS 2015 On the Pseudo-Dimension of Nearly Optimal Auctions Jamie H Morgenstern, Tim Roughgarden