# Akshay Krishnamurthy

Postdoctoral Researcher

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## Papers41 papers

Model selection for contextual bandits.

Myopic Posterior Sampling for Adaptive Goal Oriented Design of Experiments

Sample Complexity of Learning Mixture of Sparse Linear Regressions

Extreme Compressive Sampling for Covariance Estimation

On Oracle-Efficient PAC RL with Rich Observations.

An Online Hierarchical Algorithm for Extreme Clustering.

Asynchronous Parallel Bayesian Optimisation via Thompson Sampling.

Open Problem: First-Order Regret Bounds for Contextual Bandits.

A Hierarchical Algorithm for Extreme Clustering

Off-policy evaluation for slate recommendation.

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

Exploratory Gradient Boosting for Reinforcement Learning in Complex Domains.

Improved Regret Bounds for Oracle-Based Adversarial Contextual Bandits.

PAC Reinforcement Learning with Rich Observations.

Contextual semibandits via supervised learning oracles.

Minimaxity in Structured Normal Means Inference

Subspace learning from extremely compressed measurements.

Low-Rank Matrix and Tensor Completion via Adaptive Sampling.

Recovering Graph-Structured Activations using Adaptive Compressive Measurements

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

Detecting Activations over Graphs using Spanning Tree Wavelet Bases

Robust multi-source network tomography using selective probes.

Noise Thresholds for Spectral Clustering.

Fine-grained privilege separation for web applications