Gaussian Process Optimization with Adaptive Sketching: Scalable and No Regret

13 March 2019

Daniele Calandriello

Papers citing "Gaussian Process Optimization with Adaptive Sketching: Scalable and No Regret"

21 / 21 papers shown

Title
Bayesian Optimization by Kernel Regression and Density-based Exploration Tansheng Zhu Hongyu Zhou Ke Jin Xusheng Xu Qiufan Yuan Lijie Ji 248 0 0 10 Feb 2025
Differentially Private Kernelized Contextual Bandits Nikola Pavlovic Sudeep Salgia Qing Zhao 42 1 0 13 Jan 2025
An Online Learning Approach to Prompt-based Selection of Generative Models Xiaoyan Hu Ho-fung Leung Farzan Farnia 51 2 0 17 Oct 2024
Global Optimization with Parametric Function Approximation Chong Liu Yu Wang 41 7 0 16 Nov 2022
Collaborative Learning in Kernel-based Bandits for Distributed Users Sudeep Salgia Sattar Vakili Qing Zhao FedML 44 6 0 16 Jul 2022
Online SuBmodular + SuPermodular (BP) Maximization with Bandit Feedback Adhyyan Narang Omid Sadeghi Lillian J. Ratliff Maryam Fazel J. Bilmes OffRL 18 1 0 07 Jul 2022
Efficient Kernel UCB for Contextual Bandits Houssam Zenati A. Bietti Eustache Diemert Julien Mairal Matthieu Martin Pierre Gaillard 32 3 0 11 Feb 2022
Improved Convergence Rates for Sparse Approximation Methods in Kernel-Based Learning Sattar Vakili Jonathan Scarlett Da-shan Shiu A. Bernacchia 38 18 0 08 Feb 2022
Efficient Exploration in Binary and Preferential Bayesian Optimization T. Fauvel M. Chalk 35 7 0 18 Oct 2021
Uniform Generalization Bounds for Overparameterized Neural Networks Sattar Vakili Michael Bromberg Jezabel R. Garcia Da-shan Shiu A. Bernacchia 35 19 0 13 Sep 2021
Optimal Order Simple Regret for Gaussian Process Bandits Sattar Vakili N. Bouziani Sepehr Jalali A. Bernacchia Da-shan Shiu 39 51 0 20 Aug 2021
Ada-BKB: Scalable Gaussian Process Optimization on Continuous Domains by Adaptive Discretization Marco Rando Luigi Carratino S. Villa Lorenzo Rosasco 44 5 0 16 Jun 2021
Practical and Rigorous Uncertainty Bounds for Gaussian Process Regression Christian Fiedler C. Scherer Sebastian Trimpe GP 31 65 0 06 May 2021
No-Regret Algorithms for Private Gaussian Process Bandit Optimization Abhimanyu Dubey 22 13 0 24 Feb 2021
On Function Approximation in Reinforcement Learning: Optimism in the Face of Large State Spaces Zhuoran Yang Chi Jin Zhaoran Wang Mengdi Wang Michael I. Jordan 44 18 0 09 Nov 2020
Pathwise Conditioning of Gaussian Processes James T. Wilson Viacheslav Borovitskiy Alexander Terenin P. Mostowsky M. Deisenroth 18 58 0 08 Nov 2020
Asynchronous ε-Greedy Bayesian Optimisation George De Ath Richard Everson J. Fieldsend 35 5 0 15 Oct 2020
Local Differential Privacy for Bayesian Optimization Xingyu Zhou Jian Tan 22 24 0 13 Oct 2020
On Information Gain and Regret Bounds in Gaussian Process Bandits Sattar Vakili Kia Khezeli Victor Picheny GP 29 128 0 15 Sep 2020
Convergence of Sparse Variational Inference in Gaussian Processes Regression David R. Burt C. Rasmussen Mark van der Wilk 31 69 0 01 Aug 2020
Scalable Thompson Sampling using Sparse Gaussian Process Models Sattar Vakili Henry B. Moss A. Artemev Vincent Dutordoir Victor Picheny 13 34 0 09 Jun 2020