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Alekh Agarwal

85 papers · 2007–2025 · 12 conferences · across top CS/AI conferences

Achievements

πŸ—ΊοΈ Taxonomy Completionist (26) 🐝 Cross-Pollinator (13) πŸƒ Academic Marathon (18) 🌍 Conference Polyglot (12) 🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (5) 🧭 Keyword Pioneer πŸŒ‰ Interdisciplinary Bridge 🌟 Keyword Trendsetter Combo (3) 🏠 Conference Loyalist (26) πŸ† Keyword Champion (2) πŸ”¬ Deep Specialist (10) 🀝 Dynamic Duo (22) πŸ† Grand Slam πŸ‘‘ Triple Crown πŸ‘₯ Mega-Team (20) πŸ“ˆ Trend Setter ⚑ Prolific Year (10) ❓ The Questioner πŸ—ƒοΈ Keyword Collector (111) πŸš€ Conference Pioneer πŸ’Ž Century Club (85) πŸ”₯ Unstoppable (17)

Conferences

NIPS (26) ICML (25) COLT (17) JMLR (6) ICLR (3) AISTATS (2) AAAI (1) ACL (1) ALT (1) EMNLP (1) NAACL (1) UAI (1)

Top co-authors

John Langford (22) Akshay Krishnamurthy (16) Nan Jiang (10) Miroslav DudΓ­k (8) Haipeng Luo (7) Tong Zhang (7) Wen Sun (6) Robert E. Schapire (6) Martin J. Wainwright (5) Hal Daume III (5)

Keywords

regret bound (16) contextual bandit (13) online learning (11) reinforcement learning (8) sample complexity (8) representation learning (7) function approximation (7) global convergence (6) convex optimization (6) cost-sensitive classification (5) multi-armed bandit (5) policy optimization (5) active learning (4) stochastic optimization (4) multi-class classification (4) supervised learning (3) learning theory (3) importance sampling (3) policy gradient (3) model-based reinforcement learning (3)

Papers

Design Considerations in Offline Preference-based RL ICML 2025
Theoretical guarantees on the best-of-n alignment policy ICML 2025
Catoni Contextual Bandits are Robust to Heavy-tailed Rewards ICML 2025
Rewarding Progress: Scaling Automated Process Verifiers for LLM Reasoning ICLR 2025
Optimizing Pre-Training Data Mixtures with Mixtures of Data Expert Models ACL 2025
Small steps no more: Global convergence of stochastic gradient bandits for arbitrary learning rates NIPS 2024
Conditional Language Policy: A General Framework For Steerable Multi-Objective Finetuning EMNLP 2024
Model-Free Representation Learning and Exploration in Low-Rank MDPs JMLR 2024
More Benefits of Being Distributional: Second-Order Bounds for Reinforcement Learning ICML 2024
Efficient End-to-End Visual Document Understanding with Rationale Distillation NAACL 2024
A Mechanism for Sample-Efficient In-Context Learning for Sparse Retrieval Tasks ALT 2024
The Non-linear $F$-Design and Applications to Interactive Learning ICML 2024
A Minimaximalist Approach to Reinforcement Learning from Human Feedback ICML 2024
Learning in POMDPs is Sample-Efficient with Hindsight Observability ICML 2023
VO$Q$L: Towards Optimal Regret in Model-free RL with Nonlinear Function Approximation COLT 2023
Ordering-based Conditions for Global Convergence of Policy Gradient Methods NIPS 2023
Stochastic Gradient Succeeds for Bandits ICML 2023
Provable Benefits of Representational Transfer in Reinforcement Learning COLT 2023
Non-Linear Reinforcement Learning in Large Action Spaces: Structural Conditions and Sample-efficiency of Posterior Sampling COLT 2022
On the Statistical Efficiency of Reward-Free Exploration in Non-Linear RL NIPS 2022
Model-based RL with Optimistic Posterior Sampling: Structural Conditions and Sample Complexity NIPS 2022
Efficient Reinforcement Learning in Block MDPs: A Model-free Representation Learning approach ICML 2022
Minimax Regret Optimization for Robust Machine Learning under Distribution Shift COLT 2022
Provably Filtering Exogenous Distractors using Multistep Inverse Dynamics ICLR 2022
Adversarially Trained Actor Critic for Offline Reinforcement Learning ICML 2022
On the Theory of Policy Gradient Methods: Optimality, Approximation, and Distribution Shift JMLR 2021
Cautiously Optimistic Policy Optimization and Exploration with Linear Function Approximation COLT 2021
Towards a Dimension-Free Understanding of Adaptive Linear Control COLT 2021
Bellman-consistent Pessimism for Offline Reinforcement Learning NIPS 2021
Provably Correct Optimization and Exploration with Non-linear Policies ICML 2021
A Contextual Bandit Bake-off JMLR 2021
Safe Reinforcement Learning via Curriculum Induction NIPS 2020
Metareasoning in Modular Software Systems: On-the-Fly Configuration Using Reinforcement Learning with Rich Contextual Representations AAAI 2020
Provably Good Batch Off-Policy Reinforcement Learning Without Great Exploration NIPS 2020
Optimality and Approximation with Policy Gradient Methods in Markov Decision Processes COLT 2020
Model-Based Reinforcement Learning with a Generative Model is Minimax Optimal COLT 2020
Taking a hint: How to leverage loss predictors in contextual bandits? COLT 2020
Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds ICLR 2020
PC-PG: Policy Cover Directed Exploration for Provable Policy Gradient Learning NIPS 2020
FLAMBE: Structural Complexity and Representation Learning of Low Rank MDPs NIPS 2020
Policy Improvement via Imitation of Multiple Oracles NIPS 2020
Provably efficient RL with Rich Observations via Latent State Decoding ICML 2019
Fair Regression: Quantitative Definitions and Reduction-Based Algorithms ICML 2019
Active Learning for Cost-Sensitive Classification JMLR 2019
Off-Policy Policy Gradient with Stationary Distribution Correction UAI 2019
Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting NIPS 2019
Model-based RL in Contextual Decision Processes: PAC bounds and Exponential Improvements over Model-free Approaches COLT 2019
Warm-starting Contextual Bandits: Robustly Combining Supervised and Bandit Feedback ICML 2019
On Oracle-Efficient PAC RL with Rich Observations NIPS 2018
Efficient Contextual Bandits in Non-stationary Worlds COLT 2018
Practical Contextual Bandits with Regression Oracles ICML 2018
A Reductions Approach to Fair Classification ICML 2018
Open Problem: The Dependence of Sample Complexity Lower Bounds on Planning Horizon COLT 2018
Hierarchical Imitation and Reinforcement Learning ICML 2018
Off-policy evaluation for slate recommendation NIPS 2017
Active Learning for Cost-Sensitive Classification ICML 2017
Optimal and Adaptive Off-policy Evaluation in Contextual Bandits ICML 2017
Open Problem: First-Order Regret Bounds for Contextual Bandits COLT 2017
Corralling a Band of Bandit Algorithms COLT 2017
Contextual Decision Processes with low Bellman rank are PAC-Learnable ICML 2017
Efficient Second Order Online Learning by Sketching NIPS 2016
PAC Reinforcement Learning with Rich Observations NIPS 2016
Contextual semibandits via supervised learning oracles NIPS 2016
Learning to Search Better than Your Teacher ICML 2015
A Lower Bound for the Optimization of Finite Sums ICML 2015
Fast Convergence of Regularized Learning in Games NIPS 2015
Efficient and Parsimonious Agnostic Active Learning NIPS 2015
Least Squares Revisited: Scalable Approaches for Multi-class Prediction ICML 2014
Robust Multi-objective Learning with Mentor Feedback COLT 2014
Learning Sparsely Used Overcomplete Dictionaries COLT 2014
Scalable Non-linear Learning with Adaptive Polynomial Expansions NIPS 2014
A Reliable Effective Terascale Linear Learning System JMLR 2014
Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits ICML 2014
Selective sampling algorithms for cost-sensitive multiclass prediction ICML 2013
Stochastic optimization and sparse statistical recovery: Optimal algorithms for high dimensions NIPS 2012
Contextual Bandit Learning with Predictable Rewards AISTATS 2012
Distributed Delayed Stochastic Optimization NIPS 2011
Stochastic convex optimization with bandit feedback NIPS 2011
Oracle inequalities for computationally budgeted model selection COLT 2011
Optimal Allocation Strategies for the Dark Pool Problem AISTATS 2010
Fast global convergence rates of gradient methods for high-dimensional statistical recovery NIPS 2010
Distributed Dual Averaging In Networks NIPS 2010
Message-passing for Graph-structured Linear Programs: Proximal Methods and Rounding Schemes JMLR 2010
Information-theoretic lower bounds on the oracle complexity of convex optimization NIPS 2009
An Analysis of Inference with the Universum NIPS 2007