3 papers
cs.LG2025
From Invariant Representations to Invariant Data: Provable Robustness to Spurious Correlations via Noisy Counterfactual Matching
Ruqi Bai, Yao Ji, Zeyu Zhou +1
Models that learn spurious correlations from training data often fail when deployed in new environments. While many methods aim to learn invariant representations to address this,…
cs.LG2025
Robust Collaborative Inference with Vertically Split Data Over Dynamic Device Environments
Surojit Ganguli, Zeyu Zhou, Christopher G. Brinton +1
When each edge device of a network only perceives a local part of the environment, collaborative inference across multiple devices is often needed to predict global properties of t…
cs.LG2025
Counterfactual Fairness by Combining Factual and Counterfactual Predictions
Zeyu Zhou, Tianci Liu, Ruqi Bai +3
In high-stake domains such as healthcare and hiring, the role of machine learning (ML) in decision-making raises significant fairness concerns. This work focuses on Counterfactual…