Akshay Krishnamurthy

发表

Influence Functions for Machine Learning: Nonparametric Estimators for Entropies, Divergences and Mutual Informations pdf

James M. Robins, Kirthevasan Kandasamy, Akshay Krishnamurthy, 2014, ArXiv.

High-Dimensional Clustering with Sparse Gaussian Mixture Models

Akshay Krishnamurthy, A. Krishnamurthy, 2010 .

Trace Reconstruction: Generalized and Parameterized

Akshay Krishnamurthy, Arya Mazumdar, Andrew McGregor, 2019, ESA.

Minimaxity in Structured Normal Means Inference pdf

Akshay Krishnamurthy, 2015, ArXiv.

Robust multi-source network tomography using selective probes

Akshay Krishnamurthy, Aarti Singh, 2012, 2012 Proceedings IEEE INFOCOM.

Optimism in Reinforcement Learning with Generalized Linear Function Approximation pdf

Ruosong Wang, Akshay Krishnamurthy, Yining Wang, 2019, ICLR.

An Online Hierarchical Algorithm for Extreme Clustering pdf

Akshay Krishnamurthy, Andrew McCallum, Ari Kobren, 2017, ArXiv.

Corrupted Multidimensional Binary Search: Learning in the Presence of Irrational Agents pdf

Akshay Krishnamurthy, Thodoris Lykouris, Chara Podimata, 2020, ArXiv.

On the Power of Adaptivity in Matrix Completion and Approximation pdf

Akshay Krishnamurthy, Aarti Singh, 2014, ArXiv.

A Hierarchical Algorithm for Extreme Clustering

Akshay Krishnamurthy, Andrew McCallum, Ari Kobren, 2017, KDD.

On Oracle-Efficient PAC RL with Rich Observations

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

Algebraic and Analytic Approaches for Parameter Learning in Mixture Models pdf

Akshay Krishnamurthy, Soumyabrata Pal, Andrew McGregor, 2020, ALT.

Minimax structured normal means inference

Akshay Krishnamurthy, A. Krishnamurthy, 2015, 2016 IEEE International Symposium on Information Theory (ISIT).

Go for a Walk and Arrive at the Answer: Reasoning Over Paths in Knowledge Bases using Reinforcement Learning pdf

Alexander J. Smola, Akshay Krishnamurthy, Rajarshi Das, 2017, ICLR.

Contextual bandits with surrogate losses: Margin bounds and efficient algorithms

Akshay Krishnamurthy, Dylan J. Foster, A. Krishnamurthy, 2018, NeurIPS.

Efficient Contextual Semi-Bandit Learning pdf

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

Detecting Activations over Graphs using Spanning Tree Wavelet Bases

Akshay Krishnamurthy, Aarti Singh, James Sharpnack, 2012, AISTATS.

On Oracle-Efficient PAC Reinforcement Learning with Rich Observations

Nan Jiang, John Langford, Akshay Krishnamurthy, 2018 .

Myopic Bayesian Design of Experiments via Posterior Sampling and Probabilistic Programming pdf

Kirthevasan Kandasamy, Akshay Krishnamurthy, Barnabás Póczos, 2018, ArXiv.

Information Theoretic Regret Bounds for Online Nonlinear Control pdf

Akshay Krishnamurthy, Wen Sun, Motoya Ohnishi, 2020, NeurIPS.

Efficient Contextual Bandits with Continuous Actions pdf

Akshay Krishnamurthy, Aleksandrs Slivkins, Chicheng Zhang, 2020, NeurIPS.

Subspace learning from extremely compressed measurements

Akshay Krishnamurthy, Aarti Singh, Martin Azizyan, 2014, 2014 48th Asilomar Conference on Signals, Systems and Computers.

Parallelised Bayesian Optimisation via Thompson Sampling

Kirthevasan Kandasamy, Akshay Krishnamurthy, Barnabás Póczos, 2018, AISTATS.

Noise Thresholds for Spectral Clustering

Sivaraman Balakrishnan, Akshay Krishnamurthy, Min Xu, 2011, NIPS.

Learning the Linear Quadratic Regulator from Nonlinear Observations pdf

Akshay Krishnamurthy, Max Simchowitz, Dipendra Misra, 2020, NeurIPS.

Near-optimal Anomaly Detection in Graphs using Lovasz Extended Scan Statistic

Akshay Krishnamurthy, Aarti Singh, James Sharpnack, 2013, NIPS.

FLAMBE: Structural Complexity and Representation Learning of Low Rank MDPs pdf

Akshay Krishnamurthy, Wen Sun, Alekh Agarwal, 2020, NeurIPS.

Efficient Active Algorithms for Hierarchical Clustering pdf

Sivaraman Balakrishnan, Akshay Krishnamurthy, Min Xu, 2012, ICML.

Contextual Bandits with Continuous Actions: Smoothing, Zooming, and Adapting

John Langford, Akshay Krishnamurthy, Aleksandrs Slivkins, 2019, COLT.

Disagreement-based combinatorial pure exploration: Efficient algorithms and an analysis with localization pdf

Akshay Krishnamurthy, Tongyi Cao, A. Krishnamurthy, 2017, ArXiv.

Reward-Free Exploration for Reinforcement Learning

Akshay Krishnamurthy, Chi Jin, Max Simchowitz, 2020, ICML.

Off-policy evaluation for slate recommendation

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

Provably adaptive reinforcement learning in metric spaces pdf

Akshay Krishnamurthy, Tongyi Cao, 2020, NeurIPS.

Fine-grained privilege separation for web applications

David A. Wagner, Akshay Krishnamurthy, Adrian Mettler, 2010, WWW '10.

Nonparametric Estimation of Renyi Divergence and Friends

Kirthevasan Kandasamy, Akshay Krishnamurthy, Barnabás Póczos, 2014, ICML.

Semiparametric Contextual Bandits pdf

Akshay Krishnamurthy, Zhiwei Steven Wu, Vasilis Syrgkanis, 2018, ICML.

On Polynomial Time PAC Reinforcement Learning with Rich Observations pdf

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

Interactive Algorithms for Unsupervised Machine Learning

Akshay Krishnamurthy, A. Krishnamurthy, 2015 .

Nonparametric von Mises Estimators for Entropies, Divergences and Mutual Informations

James M. Robins, Kirthevasan Kandasamy, Akshay Krishnamurthy, 2015, NIPS.

Sample-Efficient Reinforcement Learning of Undercomplete POMDPs pdf

Akshay Krishnamurthy, Qinghua Liu, Sham M. Kakade, 2020, NeurIPS.

Learning to Search Better than Your Teacher pdf

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

Improved Regret Bounds for Oracle-Based Adversarial Contextual Bandits

Haipeng Luo, Akshay Krishnamurthy, Robert E. Schapire, 2016, NIPS.

Model-Based Reinforcement Learning in Contextual Decision Processes pdf

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

Contextual search in the presence of irrational agents

Akshay Krishnamurthy, Thodoris Lykouris, Chara Podimata, 2020, STOC.

Adaptive Estimator Selection for Off-Policy Evaluation pdf

Yi Su, Akshay Krishnamurthy, Pavithra Srinath, 2020, ICML.

Contrastive estimation reveals topic posterior information to linear models pdf

Akshay Krishnamurthy, Christopher Tosh, Daniel J. Hsu, 2020, J. Mach. Learn. Res..

Active Learning for Cost-Sensitive Classification

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

Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning

Akshay Krishnamurthy, Dipendra Misra, Mikael Henaff, 2019, ICML.

Exploratory Gradient Boosting for Reinforcement Learning in Complex Domains pdf

Fernando Diaz, Akshay Krishnamurthy, Robert E. Schapire, 2016, ArXiv.

Go for a Walk and Arrive at the Answer: Reasoning Over Knowledge Bases with Reinforcement Learning

Akshay Krishnamurthy, Rajarshi Das, Andrew McCallum, 2017, AKBC@NIPS.

Contrastive learning, multi-view redundancy, and linear models pdf

Akshay Krishnamurthy, Christopher Tosh, Daniel J. Hsu, 2020, ALT.

Efficient Algorithms for Adversarial Contextual Learning

Akshay Krishnamurthy, Robert E. Schapire, Vasilis Syrgkanis, 2016, ICML.

PAC Reinforcement Learning with Rich Observations

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

Myopic Posterior Sampling for Adaptive Goal Oriented Design of Experiments

Kirthevasan Kandasamy, Akshay Krishnamurthy, Barnabás Póczos, 2019, ICML.

Recovering graph-structured activations using adaptive compressive measurements

Akshay Krishnamurthy, Aarti Singh, James Sharpnack, 2013, 2013 Asilomar Conference on Signals, Systems and Computers.

Open Problem: First-Order Regret Bounds for Contextual Bandits

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

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

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

Private Reinforcement Learning with PAC and Regret Guarantees pdf

Akshay Krishnamurthy, Zhiwei Steven Wu, Borja Balle, 2020, ICML.

Open Problem: Model Selection for Contextual Bandits pdf

Haipeng Luo, Akshay Krishnamurthy, Dylan J. Foster, 2020, COLT.

Robust Dynamic Assortment Optimization in the Presence of Outlier Customers pdf

Akshay Krishnamurthy, Yining Wang, Xi Chen, 2019, ArXiv.

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

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

Low-Rank Matrix and Tensor Completion via Adaptive Sampling

Akshay Krishnamurthy, Aarti Singh, Aarti Singh, 2013, NIPS.

Contextual-MDPs for PAC-Reinforcement Learning with Rich Observations pdf

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

Contextual semibandits via supervised learning oracles

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

Asynchronous Parallel Bayesian Optimisation via Thompson Sampling pdf

Kirthevasan Kandasamy, Akshay Krishnamurthy, Barnabás Póczos, 2017, ArXiv.

Provably efficient RL with Rich Observations via Latent State Decoding pdf

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

On Estimating L22 Divergence

Kirthevasan Kandasamy, Akshay Krishnamurthy, Barnabás Póczos, 2015, AISTATS.

Scalable Hierarchical Clustering with Tree Grafting

Akshay Krishnamurthy, Andrew McCallum, Ari Kobren, 2019, KDD.

Disagreement-Based Combinatorial Pure Exploration: Sample Complexity Bounds and an Efficient Algorithm

Akshay Krishnamurthy, Tongyi Cao, A. Krishnamurthy, 2017, COLT.

Doubly robust off-policy evaluation with shrinkage pdf

Yi Su, Akshay Krishnamurthy, Miroslav Dudík, 2019, ICML.

Contrastive learning, multi-view redundancy, and linear models pdf

Akshay Krishnamurthy, Christopher Tosh, Daniel J. Hsu, 2020, ALT.

Bayesian decision-making under misspecified priors with applications to meta-learning pdf

Akshay Krishnamurthy, Robert E. Schapire, Max Simchowitz, 2021, NeurIPS.

Investigating the Role of Negatives in Contrastive Representation Learning pdf

Akshay Krishnamurthy, Jordan T. Ash, Dipendra Kumar Misra, 2021, AISTATS.

Efficient First-Order Contextual Bandits: Prediction, Allocation, and Triangular Discrimination pdf

Akshay Krishnamurthy, Dylan J. Foster, A. Krishnamurthy, 2021, NeurIPS.

Anti-Concentrated Confidence Bonuses for Scalable Exploration pdf

Akshay Krishnamurthy, Jordan T. Ash, Sham Kakade, 2021, ArXiv.

Contextual search in the presence of irrational agents

Akshay Krishnamurthy, Thodoris Lykouris, Chara Podimata, 2021, STOC.

Universal and data-adaptive algorithms for model selection in linear contextual bandits pdf

Akshay Krishnamurthy, Vidya Muthukumar, 2021, ArXiv.

Provable RL with Exogenous Distractors via Multistep Inverse Dynamics pdf

John Langford, Akshay Krishnamurthy, Alekh Agarwal, 2021, ArXiv.

Trace Reconstruction: Generalized and Parameterized

Akshay Krishnamurthy, Arya Mazumdar, Andrew McGregor, 2021, IEEE Transactions on Information Theory.

Offline Reinforcement Learning: Fundamental Barriers for Value Function Approximation pdf

David Simchi-Levi, Akshay Krishnamurthy, Dylan J. Foster, 2021, ArXiv.

Efficient and Optimal Algorithms for Contextual Dueling Bandits under Realizability pdf

Akshay Krishnamurthy, Aadirupa Saha, A. Krishnamurthy, 2021, ALT.

Gone Fishing: Neural Active Learning with Fisher Embeddings pdf

Akshay Krishnamurthy, Jordan T. Ash, Sham Kakade, 2021, NeurIPS.

Sparsity in Partially Controllable Linear Systems pdf

Akshay Krishnamurthy, Yonathan Efroni, Sham Kakade, 2021, ArXiv.

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

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

Gradient-based Hierarchical Clustering

Akshay Krishnamurthy, Andrew McCallum, Ari Kobren, 2017 .