1 citations · 1 across the 5 of their papers we have counts for
6 papers
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…
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…
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…
Kernelized Offline Contextual Dueling Bandits
Viraj Mehta, Ojash Neopane, Vikramjeet Das +3
Preference-based feedback is important for many applications where direct evaluation of a reward function is not feasible. A notable recent example arises in reinforcement learning…
Best Arm Identification under Additive Transfer Bandits
Ojash Neopane, Aaditya Ramdas, Aarti Singh
We consider a variant of the best arm identification (BAI) problem in multi-armed bandits (MAB) in which there are two sets of arms (source and target), and the objective is to det…
A Nonparametric Framework for Quantifying Generative Inference on Neuromorphic Systems
Ojash Neopane, Srinjoy Das, Ery Arias-Castro +1
Restricted Boltzmann Machines and Deep Belief Networks have been successfully used in probabilistic generative model applications such as image occlusion removal, pattern completio…