39 citations · 175 across the 48 of their papers we have counts for
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stat.ML2025
Personalized Collaborative Learning with Affinity-Based Variance Reduction
Chenyu Zhang, Navid Azizan
Multi-agent learning faces a fundamental tension: leveraging distributed collaboration without sacrificing the personalization needed for diverse agents. This tension intensifies w…
stat.ML2025
Know What You Don't Know: Uncertainty Calibration of Process Reward Models
Young-Jin Park, Kristjan Greenewald, Kaveh Alim +2
Process reward models (PRMs) play a central role in guiding inference-time scaling algorithms for large language models (LLMs). However, we observe that even state-of-the-art PRMs…
stat.ML2025
Eluder-Dimension-Free Regret for Stage-Wise Constrained Contextual Bandits via Offline Regression
Haichen Hu, David Simchi-Levi, Navid Azizan
Contextual bandits with stage-wise constraints model decisions that must control risk while learning from their outcomes. We study this problem when only the selected action's rewa…