3 papers
cs.LG2025
Sample Efficient Preference Alignment in LLMs via Active Exploration
Viraj Mehta, Syrine Belakaria, Vikramjeet Das +7
Preference-based feedback is important for many applications in machine learning where evaluation of a reward function is not feasible. Notable recent examples arise in preference…
stat.ML2025
Optimistic Algorithms for Adaptive Estimation of the Average Treatment Effect
Ojash Neopane, Aaditya Ramdas, Aarti Singh
Estimation and inference for the Average Treatment Effect (ATE) is a cornerstone of causal inference and often serves as the foundation for developing procedures for more complicat…
stat.ML2024
Logarithmic Neyman Regret for Adaptive Estimation of the Average Treatment Effect
Ojash Neopane, Aaditya Ramdas, Aarti Singh
Estimation of the Average Treatment Effect (ATE) is a core problem in causal inference with strong connections to Off-Policy Evaluation in Reinforcement Learning. This paper consid…