166 citations · 595 across the 71 of their papers we have counts for
5 papers · 2 filters
Fair Bayes-Optimal Classifiers Under Predictive Parity
Xianli Zeng, Edgar Dobriban, Guang Cheng
Increasing concerns about disparate effects of AI have motivated a great deal of work on fair machine learning. Existing works mainly focus on independence- and separation-based me…
Pursuit of a Discriminative Representation for Multiple Subspaces via Sequential Games
Druv Pai, Michael Psenka, Chih-Yuan Chiu +3
We consider the problem of learning discriminative representations for data in a high-dimensional space with distribution supported on or around multiple low-dimensional linear sub…
Collaborative Learning of Discrete Distributions under Heterogeneity and Communication Constraints
Xinmeng Huang, Donghwan Lee, Edgar Dobriban +1
In modern machine learning, users often have to collaborate to learn the distribution of the data. Communication can be a significant bottleneck. Prior work has studied homogeneous…
T-Cal: An optimal test for the calibration of predictive models
Donghwan Lee, Xinmeng Huang, Hamed Hassani +1
The prediction accuracy of machine learning methods is steadily increasing, but the calibration of their uncertainty predictions poses a significant challenge. Numerous works focus…
Bayes-Optimal Classifiers under Group Fairness
Xianli Zeng, Edgar Dobriban, Guang Cheng
Machine learning algorithms are becoming integrated into more and more high-stakes decision-making processes, such as in social welfare issues. Due to the need of mitigating the po…