Alekh Agarwal

According to our database1, Alekh Agarwal authored at least 93 papers between 2006 and 2020.

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Bibliography

2020
PC-PG: Policy Cover Directed Exploration for Provable Policy Gradient Learning.
CoRR, 2020

Provably Good Batch Reinforcement Learning Without Great Exploration.
CoRR, 2020

Policy Improvement from Multiple Experts.
CoRR, 2020

Optimizing Interactive Systems via Data-Driven Objectives.
CoRR, 2020

Safe Reinforcement Learning via Curriculum Induction.
CoRR, 2020

FLAMBE: Structural Complexity and Representation Learning of Low Rank MDPs.
CoRR, 2020

Reparameterized Variational Divergence Minimization for Stable Imitation.
CoRR, 2020

Federated Residual Learning.
CoRR, 2020

Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds.
Proceedings of the 8th International Conference on Learning Representations, 2020

Taking a hint: How to leverage loss predictors in contextual bandits?
Proceedings of the Conference on Learning Theory, 2020

Model-Based Reinforcement Learning with a Generative Model is Minimax Optimal.
Proceedings of the Conference on Learning Theory, 2020

Optimality and Approximation with Policy Gradient Methods in Markov Decision Processes.
Proceedings of the Conference on Learning Theory, 2020

Metareasoning in Modular Software Systems: On-the-Fly Configuration Using Reinforcement Learning with Rich Contextual Representations.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Active Learning for Cost-Sensitive Classification.
J. Mach. Learn. Res., 2019

On the Optimality of Sparse Model-Based Planning for Markov Decision Processes.
CoRR, 2019

Off-Policy Policy Gradient with State Distribution Correction.
CoRR, 2019

Off-Policy Policy Gradient with Stationary Distribution Correction.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Warm-starting Contextual Bandits: Robustly Combining Supervised and Bandit Feedback.
Proceedings of the 36th International Conference on Machine Learning, 2019

Provably efficient RL with Rich Observations via Latent State Decoding.
Proceedings of the 36th International Conference on Machine Learning, 2019

Fair Regression: Quantitative Definitions and Reduction-Based Algorithms.
Proceedings of the 36th International Conference on Machine Learning, 2019

Bias Correction of Learned Generative Models via Likelihood-free Importance Weighting.
Proceedings of the Deep Generative Models for Highly Structured Data, 2019

Model-based RL in Contextual Decision Processes: PAC bounds and Exponential Improvements over Model-free Approaches.
Proceedings of the Conference on Learning Theory, 2019

2018
Model-Based Reinforcement Learning in Contextual Decision Processes.
CoRR, 2018

On Polynomial Time PAC Reinforcement Learning with Rich Observations.
CoRR, 2018

Practical Evaluation and Optimization of Contextual Bandit Algorithms.
CoRR, 2018

On Oracle-Efficient PAC RL with Rich Observations.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Practical Contextual Bandits with Regression Oracles.
Proceedings of the 35th International Conference on Machine Learning, 2018

A Reductions Approach to Fair Classification.
Proceedings of the 35th International Conference on Machine Learning, 2018

Hierarchical Imitation and Reinforcement Learning.
Proceedings of the 35th International Conference on Machine Learning, 2018

Efficient Contextual Bandits in Non-stationary Worlds.
Proceedings of the Conference On Learning Theory, 2018

Open Problem: The Dependence of Sample Complexity Lower Bounds on Planning Horizon.
Proceedings of the Conference On Learning Theory, 2018

2017
A Clustering Approach to Learning Sparsely Used Overcomplete Dictionaries.
IEEE Trans. Inf. Theory, 2017

Efficient Contextual Bandits in Non-stationary Worlds.
CoRR, 2017

Off-policy evaluation for slate recommendation.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Optimal and Adaptive Off-policy Evaluation in Contextual Bandits.
Proceedings of the 34th International Conference on Machine Learning, 2017

Contextual Decision Processes with low Bellman rank are PAC-Learnable.
Proceedings of the 34th International Conference on Machine Learning, 2017

Corralling a Band of Bandit Algorithms.
Proceedings of the 30th Conference on Learning Theory, 2017

Open Problem: First-Order Regret Bounds for Contextual Bandits.
Proceedings of the 30th Conference on Learning Theory, 2017

2016
Learning Sparsely Used Overcomplete Dictionaries via Alternating Minimization.
SIAM J. Optim., 2016

Efficient Second Order Online Learning via Sketching.
CoRR, 2016

Contextual-MDPs for PAC-Reinforcement Learning with Rich Observations.
CoRR, 2016

A Multiworld Testing Decision Service.
CoRR, 2016

Exploratory Gradient Boosting for Reinforcement Learning in Complex Domains.
CoRR, 2016

Efficient Second Order Online Learning by Sketching.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

PAC Reinforcement Learning with Rich Observations.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Contextual semibandits via supervised learning oracles.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015
Efficient Contextual Semi-Bandit Learning.
CoRR, 2015

Fast Convergence of Regularized Learning in Games.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Efficient and Parsimonious Agnostic Active Learning.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Learning to Search Better than Your Teacher.
Proceedings of the 32nd International Conference on Machine Learning, 2015

A Lower Bound for the Optimization of Finite Sums.
Proceedings of the 32nd International Conference on Machine Learning, 2015

2014
A reliable effective terascale linear learning system.
J. Mach. Learn. Res., 2014

Scalable Nonlinear Learning with Adaptive Polynomial Expansions.
CoRR, 2014

Scalable Non-linear Learning with Adaptive Polynomial Expansions.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Least Squares Revisited: Scalable Approaches for Multi-class Prediction.
Proceedings of the 31th International Conference on Machine Learning, 2014

Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits.
Proceedings of the 31th International Conference on Machine Learning, 2014

Robust Multi-objective Learning with Mentor Feedback.
Proceedings of The 27th Conference on Learning Theory, 2014

Learning Sparsely Used Overcomplete Dictionaries.
Proceedings of The 27th Conference on Learning Theory, 2014

Stochastic optimization and sparse statistical recovery: An optimal algorithm for high dimensions.
Proceedings of the 48th Annual Conference on Information Sciences and Systems, 2014

2013
The Generalization Ability of Online Algorithms for Dependent Data.
IEEE Trans. Inf. Theory, 2013

Stochastic Convex Optimization with Bandit Feedback.
SIAM J. Optim., 2013

Para-active learning.
CoRR, 2013

Exact Recovery of Sparsely Used Overcomplete Dictionaries.
CoRR, 2013

Learning Sparsely Used Overcomplete Dictionaries via Alternating Minimization.
CoRR, 2013

Selective sampling algorithms for cost-sensitive multiclass prediction.
Proceedings of the 30th International Conference on Machine Learning, 2013

2012
Computational Trade-offs in Statistical Learning.
PhD thesis, 2012

Information-Theoretic Lower Bounds on the Oracle Complexity of Stochastic Convex Optimization.
IEEE Trans. Inf. Theory, 2012

Dual Averaging for Distributed Optimization: Convergence Analysis and Network Scaling.
IEEE Trans. Autom. Control., 2012

Ergodic Mirror Descent.
SIAM J. Optim., 2012

Contextual Bandit Learning with Predictable Rewards.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Oracle inequalities for computationally adaptive model selection
CoRR, 2012

FASt global convergence of gradient methods for solving regularized M-estimation.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2012

Stochastic optimization and sparse statistical recovery: Optimal algorithms for high dimensions.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Distributed delayed stochastic optimization.
Proceedings of the 51th IEEE Conference on Decision and Control, 2012

Dual averaging for distributed optimization.
Proceedings of the 50th Annual Allerton Conference on Communication, 2012

2011
Oracle inequalities for computationally budgeted model selection.
Proceedings of the COLT 2011, 2011

Fast global convergence of gradient methods for high-dimensional statistical recovery
CoRR, 2011

Online and Batch Learning Algorithms for Data with Missing Features
CoRR, 2011

Learning with Missing Features.
Proceedings of the UAI 2011, 2011

Noisy matrix decomposition via convex relaxation: Optimal rates in high dimensions.
Proceedings of the 28th International Conference on Machine Learning, 2011

2010
Message-passing for Graph-structured Linear Programs: Proximal Methods and Rounding Schemes.
J. Mach. Learn. Res., 2010

Optimal Allocation Strategies for the Dark Pool Problem.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Distributed Dual Averaging In Networks.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Fast global convergence rates of gradient methods for high-dimensional statistical recovery.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Optimal Algorithms for Online Convex Optimization with Multi-Point Bandit Feedback.
Proceedings of the COLT 2010, 2010

2009
Information-theoretic lower bounds on the oracle complexity of convex optimization.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

A Stochastic View of Optimal Regret through Minimax Duality.
Proceedings of the COLT 2009, 2009

2008
Message-passing for graph-structured linear programs: proximal projections, convergence and rounding schemes.
Proceedings of the Machine Learning, 2008

2007
An Analysis of Inference with the Universum.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Learning random walks to rank nodes in graphs.
Proceedings of the Machine Learning, 2007

2006
Learning Parameters in Entity Relationship Graphs from Ranking Preferences.
Proceedings of the Knowledge Discovery in Databases: PKDD 2006, 2006

Learning to rank networked entities.
Proceedings of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2006


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