Sattar Vakili

Julia Olkhovskaya

CoRR, 2024

Reward-Free Kernel-Based Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Random Exploration in Bayesian Optimization: Order-Optimal Regret and Computational Efficiency.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Open Problem: Order Optimal Regret Bounds for Kernel-Based Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

Optimal Regret Bounds for Collaborative Learning in Bandits.

[BibT_eX]

[DOI]

Amitis Shidani

Proceedings of the International Conference on Algorithmic Learning Theory, 2024

Adversarial Contextual Bandits Go Kernelized.

[BibT_eX]

[DOI]

Gergely Neu

Julia Olkhovskaya

Proceedings of the International Conference on Algorithmic Learning Theory, 2024

2023

Collaborative Learning in Kernel-Based Bandits for Distributed Users.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2023

Robust Best-arm Identification in Linear Bandits.

[BibT_eX]

[DOI]

Wei Wang

Ilija Bogunovic

CoRR, 2023

Trieste: Efficiently Exploring The Depths of Black-box Functions with TensorFlow.

[BibT_eX]

[DOI]

Nasrulloh R. B. S. Loka

Ivo Couckuyt

CoRR, 2023

Kernelized Reinforcement Learning with Order Optimal Regret Bounds.

[BibT_eX]

[DOI]

Julia Olkhovskaya

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Information Gain and Uniform Generalization Bounds for Neural Kernel Models.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2023

Delayed Feedback in Kernel Bandits.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Image generation with shortest path diffusion.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Fisher-Legendre (FishLeg) optimization of deep neural networks.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Generative Diffusion Models for Radio Wireless Channel Modelling and Sampling.

[BibT_eX]

[DOI]

Proceedings of the IEEE Global Communications Conference, 2023

Sample Complexity of Kernel-Based Q-Learning.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Kernel-based Federated Learning with Personalization.

[BibT_eX]

[DOI]

CoRR, 2022

Provably and Practically Efficient Neural Contextual Bandits.

[BibT_eX]

[DOI]

CoRR, 2022

Near-Optimal Collaborative Learning in Bandits.

[BibT_eX]

[DOI]

Clémence Réda

Emilie Kaufmann

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Improved Convergence Rates for Sparse Approximation Methods in Kernel-Based Learning.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

2021

Uniform Generalization Bounds for Overparameterized Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2021

Scalable Thompson Sampling using Sparse Gaussian Process Models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Optimal Order Simple Regret for Gaussian Process Bandits.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A Domain-Shrinking based Bayesian Optimization Algorithm with Order-Optimal Regret Performance.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Open Problem: Tight Online Confidence Intervals for RKHS Elements.

[BibT_eX]

[DOI]

Filipo Studzinski Perotto

Jonathan Scarlett

Tara Javidi

Proceedings of the Conference on Learning Theory, 2021

Gambler Bandits and the Regret of Being Ruined.

[BibT_eX]

[DOI]

Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

On Information Gain and Regret Bounds in Gaussian Process Bandits.

[BibT_eX]

[DOI]

Kia Khezeli

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Multi-Armed Bandits on Partially Revealed Unit Interval Graphs.

[BibT_eX]

[DOI]

IEEE Trans. Netw. Sci. Eng., 2020

A Computationally Efficient Approach to Black-box Optimization using Gaussian Process Models.

[BibT_eX]

[DOI]

CoRR, 2020

Scalable Thompson Sampling using Sparse Gaussian Process Models.

[BibT_eX]

[DOI]

Artem Artemev

CoRR, 2020

Amortized variance reduction for doubly stochastic objectives.

[BibT_eX]

[DOI]

CoRR, 2020

Regret Bounds for Noise-Free Bayesian Optimization.

[BibT_eX]

[DOI]

Nicolas Durrande

CoRR, 2020

Amortized variance reduction for doubly stochastic objective.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Stochastic Coordinate Minimization with Progressive Precision for Stochastic Convex Optimization.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Ordinal Bayesian Optimisation.

[BibT_eX]

[DOI]

Artem Artemev

CoRR, 2019

A Random Walk Approach to First-Order Stochastic Convex Optimization.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2019

Adaptive Sensor Placement for Continuous Spaces.

[BibT_eX]

[DOI]

Enrique Munoz de Cote

Proceedings of the 36th International Conference on Machine Learning, 2019

Decision Variance in Risk-Averse Online Learning.

[BibT_eX]

[DOI]

Alexis Boukouvalas

Proceedings of the 58th IEEE Conference on Decision and Control, 2019

Stochastic Gradient Descent on a Tree: an Adaptive and Robust Approach to Stochastic Convex Optimization.

[BibT_eX]

[DOI]

Proceedings of the 57th Annual Allerton Conference on Communication, 2019

2018

Decision Variance in Online Learning.

[BibT_eX]

[DOI]

Alexis Boukouvalas

CoRR, 2018

Multi-Armed Bandits on Unit Interval Graphs.

[BibT_eX]

[DOI]

CoRR, 2018

Hierarchical Heavy Hitter Detection Under Unknown Models.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

2017

Anomaly Detection in Hierarchical Data Streams under Unknown Models.

[BibT_eX]

[DOI]

CoRR, 2017

Online learning with side information.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE Military Communications Conference, 2017

2016

Risk-Averse Multi-Armed Bandit Problems Under Mean-Variance Measure.

[BibT_eX]

[DOI]

IEEE J. Sel. Top. Signal Process., 2016

2015

Quickest detection of short-term voltage instability with PMU measurements.

[BibT_eX]

[DOI]

Lang Tong

Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Risk-averse online learning under mean-variance measures.

[BibT_eX]

[DOI]

Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Bayesian quickest short-term voltage instability detection in power systems.

[BibT_eX]

[DOI]

Lang Tong

Proceedings of the 54th IEEE Conference on Decision and Control, 2015

Mean-variance and value at risk in multi-armed bandit problems.

[BibT_eX]

[DOI]

Proceedings of the 53rd Annual Allerton Conference on Communication, 2015

2014

Time-varying stochastic multi-armed bandit problems.

[BibT_eX]

[DOI]

Yuan Zhou

Proceedings of the 48th Asilomar Conference on Signals, Systems and Computers, 2014

2013

Deterministic Sequencing of Exploration and Exploitation for Multi-Armed Bandit Problems.

[BibT_eX]

[DOI]

Keqin Liu

IEEE J. Sel. Top. Signal Process., 2013

Achieving complete learning in Multi-Armed Bandit problems.

[BibT_eX]

[DOI]

Proceedings of the 2013 Asilomar Conference on Signals, 2013

Distributed node-weighted connected dominating set problems.

[BibT_eX]

[DOI]