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Selected Publications
- Kernel-Based Function Approximation for Average Reward Reinforcement Learning: An Optimist No-Regret Algorithm, NeurIPS 2024
- Open Problem: Order Optimal Regret Bounds for Kernel-Based Reinforcement Learning, COLT 2024
- Reward-Free Kernel-Based Reinforcement Learning, ICML 2024
- Random Exploration in Bayesian Optimization: Order-Optimal Regret and Computational Efficiency, ICML 2024
- Optimal Regret Bounds for Collaborative Learning in Bandits, Algorithmic Learning Theory (ALT) 2024
- Adversarial Contextual Bandits Go Kernelized, Algorithmic Learning Theory (ALT) 2024
- Kernelized Reinforcement Learning with Order Optimal Regret Bounds, NeurIPS 2023 (Part of this work was presented at EWRL 2023)
- Collaborative Learning in Kernel-based Bandits for Distributed Users, IEEE Transactions on Signal Processing 2023
- Delayed Feedback in Kernel Bandits, ICML 2023, [presentation]
- Provably and Practically Efficient Neural Contextual Bandits, ICML 2023
- Image generation with shortest path diffusion, ICML 2023
- Sample Complexity of Kernel-Based Q-Learning, AISTATS 2023
- Fisher-Legendre (FishLeg) optimization of deep neural networks, ICLR 2023
- Uniform generalization bounds for overparameterized neural networks, ISIT 2023
- Generative Diffusion Models for Radio Wireless Channel Modelling and Sampling, GLOBECOM 2023
- Near-Optimal Collaborative Learning in Bandits, NeurIPS 2022, [presentation]
- Improved convergence rates for sparse approximation methods in kernel-based learning, ICML 2022, [presentation]
- On Information Gain and Regret Bounds in GP Bandits, AISTATS 2021, [slides], [presentation]
- Optimal order simple regret for GP bandits, NeurIPS 2021, [slides], [presentation]
- Scalable Thompson sampling using sparse Gaussian process models, NeurIPS 2021, [slides], [presentation]
- Open problem: Tight online confidence intervals for RKHS elements, COLT 2021, [slides], [presentation]
- A domain-shrinking based Bayesian optimization algorithm with orderoptimal regret performance, NeurIPS 2021
- Stochastic Coordinate Minimization with Progressive Precision for Stochastic Convex Optimization, ICML 2020
- Amortized variance reduction for doubly stochastic objective, UAI 2020
- Adaptive sensor placement for continuous spaces, ICML 2019
- Multi-armed bandits on partially revealed unit interval graphs, IEEE Transactions on Network Science and Engineering 2019
- A random walk approach to first-order stochastic convex optimization, ISIT 2019
- Decision variance in risk-averse online learning, CDC 2019
- Hierarchical heavy hitter detection under unknown models, ICASSP 2018
- Online learning with side information, MILCOM 2017
- Risk-averse multi-armed bandit problems under mean-variance measure, Journal of Slected Topic in Signal Processing 2016
- Quickest detection of short-term voltage instability with PMU measurements, ICASSP 2015
- Time-varying stochastic multi-armed bandit problems, Asilomar 2014
- Deterministic sequencing of exploration and exploitation for multi-armed bandit problems, Journal of Selected Topics in Signal Processing 2013
- Achieving complete learning in multi-armed bandit problems, Asilomar 2013
