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Alekh Agarwal — most-cited papers & profile · Reinforcement Learning
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Alekh Agarwal
24
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41
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Most-cited papers
Ordering-based Conditions for Global Convergence of Policy Gradient Methods
2025
Catoni Contextual Bandits are Robust to Heavy-tailed Rewards
2025
Off-policy evaluation for slate recommendation
2016
Corralling a Band of Bandit Algorithms
2016
A Contextual Bandit Bake-off
2018
Practical Contextual Bandits with Regression Oracles
2018
Warm-starting Contextual Bandits: Robustly Combining Supervised and Bandit Feedback
2019
Taking a hint: How to leverage loss predictors in contextual bandits?
2020
Optimizing Interactive Systems via Data-Driven Objectives
2020
Policy Improvement via Imitation of Multiple Oracles
2020
Towards a Dimension-Free Understanding of Adaptive Linear Control
2021
Learning in POMDPs is Sample-Efficient with Hindsight Observability
2023
Leveraging User-Triggered Supervision in Contextual Bandits
2023
An Empirical Evaluation of Federated Contextual Bandit Algorithms
2023
Robust Preference Optimization through Reward Model Distillation
2024
Top co-authors
Haipeng Luo
· 3
John Langford
· 3
Christoph Dann
· 2
Miroslav Dud\'ik
· 2
Tong Zhang
· 2
Adam Fisch
· 1
Adith Swaminathan
· 1
Ahmad Beirami
· 1
Akshay Krishnamurthy
· 1
Alberto Bietti
· 1
Alexandre Ram\'e
· 1
Amr Ahmed
· 1
Topics
cs.LG
Exploration
stat.ML
Policy Gradient
Meta-RL
cs.AI
Offline RL
Value-Based
Model-Based RL
cs.CL