Philip S. Thomas

Associate Professor, College of Information and Computer Science, University of Massachusetts, Amherst

3 papers at NeurIPS 2025

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Poster Session 1

2 papers

Wednesday, December 3, 2025 · 11:00 AM → 2:00 PM

Exhibit Hall C,D,E

Fair Representation Learning with Controllable High Confidence Guarantees via Adversarial Inference

#1411 · Yuhong Luo, Austin Hoag, Xintong Wang, Philip S. Thomas, Przemyslaw A. Grabowicz

We introduce a representation learning framework that provides high-confidence fairness guarantees with controllable error thresholds and confidence levels via adversarial inference.

Fair Continuous Resource Allocation with Equality of Impact

#1100 · Blossom Metevier, Dennis Wei, Karthikeyan Natesan Ramamurthy, Philip S. Thomas

Poster Session 2

1 paper

Wednesday, December 3, 2025 · 4:30 PM → 7:30 PM

Exhibit Hall C,D,E

Beyond Prediction: Managing the Repercussions of Machine Learning Applications

#1408 · Aline Weber, Blossom Metevier, Yuriy Brun, Philip S. Thomas, Bruno Castro da Silva