Alekh Agarwal

发表

Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits

John Langford, Lihong Li, Robert E. Schapire, 2014, ICML.

On the Theory of Policy Gradient Methods: Optimality, Approximation, and Distribution Shift

Sham M. Kakade, Jason D. Lee, Gaurav Mahajan, 2019, J. Mach. Learn. Res..

Distributed delayed stochastic optimization

John C. Duchi, Alekh Agarwal, Alekh Agarwal, 2011, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).

Learning with Missing Features

Peter L. Bartlett, Afshin Rostamizadeh, Alekh Agarwal, 2011, UAI.

A reliable effective terascale linear learning system

John Langford, Miroslav Dudík, Alekh Agarwal, 2011, J. Mach. Learn. Res..

Distributed Dual Averaging In Networks

Martin J. Wainwright, John C. Duchi, Alekh Agarwal, 2010, NIPS.

Optimality and Approximation with Policy Gradient Methods in Markov Decision Processes

Sham M. Kakade, Jason D. Lee, Gaurav Mahajan, 2019, COLT.

Oracle inequalities for computationally adaptive model selection pdf

Peter L. Bartlett, John C. Duchi, Alekh Agarwal, 2012, ArXiv.

A Multiworld Testing Decision Service pdf

John Langford, Stephen Lee, Siddhartha Sen, 2016, ArXiv.

Making Contextual Decisions with Low Technical Debt

John Langford, Stephen Lee, Siddhartha Sen, 2016 .

Information-theoretic lower bounds on the oracle complexity of sparse convex optimization

Pradeep Ravikumar, Alekh Agarwal, 2010 .

Safe Reinforcement Learning via Curriculum Induction

Alekh Agarwal, S. Shah, A. Krause, 2020, NeurIPS.

Information-Theoretic Lower Bounds on the Oracle Complexity of Stochastic Convex Optimization

Martin J. Wainwright, Pradeep Ravikumar, Peter L. Bartlett, 2010, IEEE Transactions on Information Theory.

Dual Averaging for Distributed Optimization: Convergence Analysis and Network Scaling

Martin J. Wainwright, John C. Duchi, Alekh Agarwal, 2010, IEEE Transactions on Automatic Control.

A Stochastic View of Optimal Regret through Minimax Duality pdf

Peter L. Bartlett, Alekh Agarwal, Jacob D. Abernethy, 2009, COLT.

Hierarchical Imitation and Reinforcement Learning pdf

Nan Jiang, Yisong Yue, Miroslav Dudík, 2018, ICML.

Sentiment Analysis : A New Approach for Effective Use of Linguistic Knowledge and Exploiting Similarities in a Set of Documents to be Classified .

Alekh Agarwal, 2005 .

Fast global convergence of gradient methods for high-dimensional statistical recovery pdf

Martin J. Wainwright, Alekh Agarwal, Sahand N. Negahban, 2011, ArXiv.

Learning Sparsely Used Overcomplete Dictionaries via Alternating Minimization

Prateek Jain, Praneeth Netrapalli, Animashree Anandkumar, 2013, SIAM J. Optim..

Optimal Allocation Strategies for the Dark Pool Problem

Peter L. Bartlett, Alekh Agarwal, Max Dama, 2010, AISTATS.

Off-policy evaluation for slate recommendation

John Langford, Akshay Krishnamurthy, Miroslav Dudík, 2016, NIPS.

Exact Recovery of Sparsely Used Overcomplete Dictionaries pdf

Anima Anandkumar, Praneeth Netrapalli, Alekh Agarwal, 2013, ArXiv.

Ergodic mirror descent

Michael I. Jordan, John C. Duchi, Alekh Agarwal, 2011, 2011 49th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

A Contextual Bandit Bake-off

John Langford, Alekh Agarwal, Alberto Bietti, 2018, J. Mach. Learn. Res..

Learning Sparsely Used Overcomplete Dictionaries

Prateek Jain, Anima Anandkumar, Praneeth Netrapalli, 2014, COLT.

Optimal and Adaptive Off-policy Evaluation in Contextual Bandits pdf

Miroslav Dudík, Yu-Xiang Wang, Alekh Agarwal, 2016, ICML.

A Reductions Approach to Fair Classification pdf

John Langford, Miroslav Dudík, Hanna M. Wallach, 2018, ICML.

Noisy matrix decomposition via convex relaxation: Optimal rates in high dimensions

Martin J. Wainwright, Alekh Agarwal, Sahand N. Negahban, 2011, ICML.

Reinforcement Learning: Theory and Algorithms

S. Kakade, Alekh Agarwal, Nan Jiang, 2019 .

Fast global convergence rates of gradient methods for high-dimensional statistical recovery

Martin J. Wainwright, Alekh Agarwal, Sahand N. Negahban, 2010, NIPS.

Learning Parameters in Entity Relationship Graphs from Ranking Preferences

Soumen Chakrabarti, Alekh Agarwal, Alekh Agarwal, 2006, PKDD.

Augmenting WordNet with Polarity Information on Adjectives

Pushpak Bhattacharyya, Alekh Agarwal, Alekh Agarwal, 2006 .

Optimality and Approximation with Policy Gradient Methods in Markov Decision Processes

S. Kakade, J. Lee, Alekh Agarwal, 2019, COLT.

Policy Improvement via Imitation of Multiple Oracles

Andrey Kolobov, Ching-An Cheng, Alekh Agarwal, 2020, NeurIPS.

J ul 2 01 4 A Clustering Approach to Learn Sparsely-Used Overcomplete Dictionaries

Praneeth Netrapalli, Alekh Agarwal, Anima Anandkumar, 2014 .

A Lower Bound for the Optimization of Finite Sums

Léon Bottou, Alekh Agarwal, L. Bottou, 2014, ICML.

AReductionsApproach to FairClassification

J. Langford, Alekh Agarwal, Miroslav Dudík, 2017 .

Provably Good Batch Off-Policy Reinforcement Learning Without Great Exploration

Emma Brunskill, Adith Swaminathan, Alekh Agarwal, 2020, NeurIPS.

Bellman-consistent Pessimism for Offline Reinforcement Learning

Alekh Agarwal, Nan Jiang, Paul Mineiro, 2021, Neural Information Processing Systems.

Provable Benefits of Representational Transfer in Reinforcement Learning

Alekh Agarwal, Wen Sun, Mengdi Wang, 2022, ArXiv.

Model-based RL with Optimistic Posterior Sampling: Structural Conditions and Sample Complexity

Alekh Agarwal, T. Zhang, 2022, ArXiv.

Adversarially Trained Actor Critic for Offline Reinforcement Learning

Alekh Agarwal, Nan Jiang, Tengyang Xie, 2022, ICML.

L G ] 4 J ul 2 01 9 On the Optimality of Sparse Model-Based Planning for Markov Decision Processes

Alekh Agarwal, 2019 .

Ergodic Subgradient Descent

Michael I. Jordan, John C. Duchi, Alekh Agarwal, 2011 .

MULTISTEP INVERSE DYNAMICS

Dipendra Kumar Misra, J. Langford, A. Krishnamurthy, 2022 .

Model-based RL with Optimistic Posterior Sampling: Structural Conditions and Sample Complexity

Alekh Agarwal, T. Zhang, 2022, ArXiv.

Model-based RL with Optimistic Posterior Sampling: Structural Conditions and Sample Complexity

Alekh Agarwal, T. Zhang, 2022, NeurIPS.

Efficient Reinforcement Learning in Block MDPs: A Model-free Representation Learning Approach

Alekh Agarwal, Masatoshi Uehara, Wen Sun, 2022, ICML.

Model-free Representation Learning and Exploration in Low-rank MDPs

A. Krishnamurthy, Alekh Agarwal, Nan Jiang, 2021, ArXiv.

On the Statistical Efficiency of Reward-Free Exploration in Non-Linear RL

A. Krishnamurthy, Alekh Agarwal, Nan Jiang, 2022, NeurIPS.

A Clustering Approach to Learning Sparsely Used Overcomplete Dictionaries

Praneeth Netrapalli, Animashree Anandkumar, Alekh Agarwal, 2013, IEEE Transactions on Information Theory.

Fair Regression: Quantitative Definitions and Reduction-based Algorithms

Miroslav Dudík, Zhiwei Steven Wu, Alekh Agarwal, 2019, ICML.

Non-Linear Reinforcement Learning in Large Action Spaces: Structural Conditions and Sample-efficiency of Posterior Sampling

Alekh Agarwal, T. Zhang, 2022, COLT.

Para-active learning pdf

John Langford, Miroslav Dudík, Léon Bottou, 2013, ArXiv.

Stochastic optimization and sparse statistical recovery: An optimal algorithm for high dimensions

Martin J. Wainwright, Alekh Agarwal, Sahand N. Negahban, 2012, 2014 48th Annual Conference on Information Sciences and Systems (CISS).

A ug 2 01 2 Oracle inequalities for computationally adaptive model selection

John C. Duchi, P. Bartlett, Alekh Agarwal, 2012 .

Computational Trade-offs in Statistical Learning

Alekh Agarwal, Alekh Agarwal, 2012 .

Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds pdf

John Langford, Alekh Agarwal, Jordan T. Ash, 2019, ICLR.

Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting

Eric Horvitz, Ashish Kapoor, Stefano Ermon, 2019, DGS@ICLR.

Dual averaging for distributed optimization

Martin J. Wainwright, John C. Duchi, Alekh Agarwal, 2012, 2012 50th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

Learning to Search Better than Your Teacher pdf

John Langford, Akshay Krishnamurthy, Kai-Wei Chang, 2015, ICML.

Safe Reinforcement Learning via Curriculum Induction pdf

Andrey Kolobov, Alekh Agarwal, Andreas Krause, 2020, NeurIPS.

Contextual Decision Processes with low Bellman rank are PAC-Learnable pdf

Nan Jiang, John Langford, Akshay Krishnamurthy, 2016, ICML.

Optimal Algorithms for Online Convex Optimization with Multi-Point Bandit Feedback.

Lin Xiao, Alekh Agarwal, Ofer Dekel, 2010, COLT 2010.

Efficient Second Order Online Learning by Sketching

Haipeng Luo, Nicolò Cesa-Bianchi, Alekh Agarwal, 2016, NIPS.

Model-based RL in Contextual Decision Processes: PAC bounds and Exponential Improvements over Model-free Approaches

Nan Jiang, John Langford, Akshay Krishnamurthy, 2018, COLT.

On Oracle-Efficient PAC RL with Rich Observations

Nan Jiang, John Langford, Akshay Krishnamurthy, 2018, NeurIPS.

PAC Reinforcement Learning with Rich Observations

John Langford, Akshay Krishnamurthy, Alekh Agarwal, 2016, NIPS.

Metareasoning in Modular Software Systems: On-the-Fly Configuration using Reinforcement Learning with Rich Contextual Representations

Eric Horvitz, Sean Andrist, Debadeepta Dey, 2019, AAAI.

Provably Good Batch Reinforcement Learning Without Great Exploration pdf

Emma Brunskill, Adith Swaminathan, Alekh Agarwal, 2020, ArXiv.

Provably efficient RL with Rich Observations via Latent State Decoding pdf

Nan Jiang, John Langford, Akshay Krishnamurthy, 2019, ICML.

Cautiously Optimistic Policy Optimization and Exploration with Linear Function Approximation

Alekh Agarwal, Andrea Zanette, Ching-An Cheng, 2021, COLT.

FLAMBE: Structural Complexity and Representation Learning of Low Rank MDPs

S. Kakade, A. Krishnamurthy, Alekh Agarwal, 2020, NeurIPS.

Model-Based Reinforcement Learning with a Generative Model is Minimax Optimal

Lin F. Yang, S. Kakade, Alekh Agarwal, 2019, COLT.

PC-PG: Policy Cover Directed Exploration for Provable Policy Gradient Learning pdf

Wen Sun, Alekh Agarwal, Mikael Henaff, 2020, NeurIPS.

Oracle inequalities for computationally budgeted model selection

Peter L. Bartlett, John C. Duchi, Alekh Agarwal, 2011, COLT.

Message-passing for Graph-structured Linear Programs: Proximal Methods and Rounding Schemes

Martin J. Wainwright, Pradeep Ravikumar, Alekh Agarwal, 2010, J. Mach. Learn. Res..

Stochastic Convex Optimization with Bandit Feedback

Sham M. Kakade, Dean P. Foster, Alekh Agarwal, 2011, SIAM J. Optim..

Information-theoretic lower bounds on the oracle complexity of convex optimization

Martin J. Wainwright, Pradeep Ravikumar, Peter L. Bartlett, 2009, NIPS.

Federated Residual Learning pdf

Chen-Yu Wei, Alekh Agarwal, John Langford, 2020, ArXiv.

An Empirical Evaluation of Federated Contextual Bandit Algorithms

H. B. McMahan, Alekh Agarwal, Zheng Xu, 2023, ArXiv.

VOQL: Towards Optimal Regret in Model-free RL with Nonlinear Function Approximation

Alekh Agarwal, Tong Zhang, Yujia Jin, 2022, ArXiv.

Fast Convergence of Regularized Learning in Games

Haipeng Luo, Robert E. Schapire, Vasilis Syrgkanis, 2015, NIPS.

Learning random walks to rank nodes in graphs

Soumen Chakrabarti, Alekh Agarwal, Alekh Agarwal, 2007, ICML '07.

A Mechanism for Sample-Efficient In-Context Learning for Sparse Retrieval Tasks

Manfred K. Warmuth, Jacob D. Abernethy, Alekh Agarwal, 2023, ArXiv.

The Generalization Ability of Online Algorithms for Dependent Data

John C. Duchi, Alekh Agarwal, Alekh Agarwal, 2011, IEEE Transactions on Information Theory.

Least Squares Revisited: Scalable Approaches for Multi-class Prediction

Le Song, Nikos Karampatziakis, Sham M. Kakade, 2013, ICML.

On the Optimality of Sparse Model-Based Planning for Markov Decision Processes pdf

Lin F. Yang, Alekh Agarwal, Sham Kakade, 2019, ArXiv.

Corralling a Band of Bandit Algorithms pdf

Haipeng Luo, Robert E. Schapire, Behnam Neyshabur, 2016, COLT.

Off-Policy Policy Gradient with State Distribution Correction pdf

Emma Brunskill, Yao Liu, Adith Swaminathan, 2019, UAI 2019.

An Analysis of Inference with the Universum

Bernhard Schölkopf, Alekh Agarwal, Olivier Chapelle, 2007, NIPS.

Practical Contextual Bandits with Regression Oracles pdf

Haipeng Luo, Miroslav Dudík, Robert E. Schapire, 2018, ICML.

Learning to rank networked entities

Soumen Chakrabarti, Alekh Agarwal, Sunny Aggarwal, 2006, KDD '06.

Active Learning for Cost-Sensitive Classification

John Langford, Akshay Krishnamurthy, Tzu-Kuo Huang, 2017, ICML.

Efficient and Parsimonious Agnostic Active Learning

John Langford, Robert E. Schapire, Tzu-Kuo Huang, 2015, NIPS.

Efficient Contextual Bandits in Non-stationary Worlds pdf

Haipeng Luo, Alekh Agarwal, John Langford, 2017, COLT.

Learning in POMDPs is Sample-Efficient with Hindsight Observability

Alekh Agarwal, T. Zhang, Christoph Dann, 2023, ICML.

Open Problem: The Dependence of Sample Complexity Lower Bounds on Planning Horizon

Nan Jiang, Alekh Agarwal, Alekh Agarwal, 2018, COLT.

Provable Benefits of Representational Transfer in Reinforcement Learning

Alekh Agarwal, Wen Sun, Mengdi Wang, 2022, COLT.

Provably Correct Optimization and Exploration with Non-linear Policies

Wotao Yin, Alekh Agarwal, Fei Feng, 2021, ICML.

Scalable Non-linear Learning with Adaptive Polynomial Expansions

John Langford, Matus Telgarsky, Alekh Agarwal, 2014, NIPS.

Open Problem: First-Order Regret Bounds for Contextual Bandits

John Langford, Haipeng Luo, Akshay Krishnamurthy, 2017, COLT.

Selective sampling algorithms for cost-sensitive multiclass prediction

Alekh Agarwal, Alekh Agarwal, 2013, ICML.

Off-Policy Policy Gradient with Stationary Distribution Correction

Yao Liu, Emma Brunskill, Adith Swaminathan, 2019, UAI.

Lecture Notes on the Theory of Reinforcement Learning

S. Kakade, Alekh Agarwal, Nan Jiang, 2019 .

Lectures on the Theory of Reinforcement Learning

S. Kakade, Alekh Agarwal, Nan Jiang, 2019 .

Model-based RL in Contextual Decision Processes: PAC bounds and Exponential Improvements over Model-free Approaches

J. Langford, A. Krishnamurthy, Alekh Agarwal, 2018, COLT.

Contextual Bandit Learning with Predictable Rewards pdf

John Langford, Miroslav Dudík, Robert E. Schapire, 2012, AISTATS.

Provably Filtering Exogenous Distractors using Multistep Inverse Dynamics

Dipendra Kumar Misra, J. Langford, A. Krishnamurthy, 2022, International Conference on Learning Representations.

L G ] 2 9 A ug 2 01 9 Optimality and Approximation with Policy Gradient Methods in Markov Decision Processes

S. Kakade, J. Lee, Alekh Agarwal, 2019 .

Dual Averaging for Distributed Optimization: Convergence Analysis and Network Scaling

John C. Duchi, M. Wainwright, Alekh Agarwal, 2010, IEEE Transactions on Automatic Control.

On Oracle-Efficient PAC Reinforcement Learning with Rich Observations

Nan Jiang, John Langford, Akshay Krishnamurthy, 2018 .

On Polynomial Time PAC Reinforcement Learning with Rich Observations pdf

Nan Jiang, John Langford, Akshay Krishnamurthy, 2018, ArXiv.

Minimax Regret Optimization for Robust Machine Learning under Distribution Shift

Alekh Agarwal, Tong Zhang, 2022, COLT.

Ieee Transactions on Automatic Control 1 Dual Averaging for Distributed Optimization: Convergence Analysis and Network Scaling

John C. Duchi, M. Wainwright, Alekh Agarwal, 2022 .

Reparameterized Variational Divergence Minimization for Stable Imitation pdf

Asli Çelikyilmaz, Debadeepta Dey, William B. Dolan, 2020, ArXiv.

Contextual semibandits via supervised learning oracles

Akshay Krishnamurthy, Miroslav Dudík, Alekh Agarwal, 2015, NIPS.

Efficient Contextual Semi-Bandit Learning pdf

Akshay Krishnamurthy, Miroslav Dudík, Alekh Agarwal, 2015, ArXiv.

Warm-starting Contextual Bandits: Robustly Combining Supervised and Bandit Feedback pdf

John Langford, Hal Daumé, Alekh Agarwal, 2019, ICML.

Exploratory Gradient Boosting for Reinforcement Learning in Complex Domains

R. Schapire, A. Krishnamurthy, Alekh Agarwal, 2016, ArXiv.

Optimal Algorithms for Online Convex Optimization with Multi-Point Bandit Feedback.

O. Dekel, Alekh Agarwal, Lin Xiao, 2010, COLT 2010.

Matrix regularization techniques for online multitask learning

Peter L. Bartlett, Alekh Agarwal, Alexander Rakhlin, 2008 .

Stochastic optimization with noni . i . d . noise

John C. Duchi, Alekh Agarwal, 2011 .

Information-theoretic lower bounds on the oracle complexity of sparse convex optimization

Pradeep Ravikumar, Alekh Agarwal, 2010 .

A Reductions Approach to Fair Classification

Hanna M. Wallach, J. Langford, Alekh Agarwal, 2018, ICML.

Learning to Search Better than Your Teacher

J. Langford, A. Krishnamurthy, Alekh Agarwal, 2015, ICML.

Oracle inequalities for computationally budgeted model selection

John C. Duchi, Alekh Agarwal, Peter L. Bartlett, 2011, COLT.

Bellman-consistent Pessimism for Offline Reinforcement Learning

Alekh Agarwal, Nan Jiang, Paul Mineiro, 2021, NeurIPS.

Online and Batch Learning Algorithms for Data with Missing Features

P. Bartlett, Afshin Rostamizadeh, Alekh Agarwal, 2011, ArXiv.