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

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

8 February 2022

Jonathan Scarlett

Papers citing "Improved Convergence Rates for Sparse Approximation Methods in Kernel-Based Learning"

18 / 18 papers shown

Title
Distributionally Robust Active Learning for Gaussian Process Regression Shion Takeno Yoshito Okura Yu Inatsu Aoyama Tatsuya Tomonari Tanaka ... Noriaki Hashimoto Taro Murayama Hanju Lee Shinya Kojima Ichiro Takeuchi OOD GP 43 0 0 24 Feb 2025
Differentially Private Kernelized Contextual Bandits Nikola Pavlovic Sudeep Salgia Qing Zhao 40 1 0 13 Jan 2025
Adaptive Resource Allocation for Virtualized Base Stations in O-RAN with Online Learning Michail Kalntis Georgios Iosifidis Fernando A. Kuipers 39 5 0 31 Dec 2024
Kernel-Based Function Approximation for Average Reward Reinforcement Learning: An Optimist No-Regret Algorithm Sattar Vakili Julia Olkhovskaya 33 0 0 30 Oct 2024
A variational Bayes approach to debiased inference for low-dimensional parameters in high-dimensional linear regression Ismaël Castillo Alice L'Huillier Kolyan Ray Luke Travis 39 0 0 18 Jun 2024
Further Understanding of a Local Gaussian Process Approximation: Characterising Convergence in the Finite Regime Anthony Stephenson Robert Allison Edward O. Pyzer-Knapp 29 0 0 09 Apr 2024
Order-Optimal Regret in Distributed Kernel Bandits using Uniform Sampling with Shared Randomness Nikola Pavlovic Sudeep Salgia Qing Zhao 45 1 0 20 Feb 2024
Variational Gaussian Processes For Linear Inverse Problems Thibault Randrianarisoa Botond Szabó 43 3 0 01 Nov 2023
Pointwise uncertainty quantification for sparse variational Gaussian process regression with a Brownian motion prior Luke Travis Kolyan Ray 24 4 0 29 Sep 2023
Kernelized Reinforcement Learning with Order Optimal Regret Bounds Sattar Vakili Julia Olkhovskaya 23 9 0 13 Jun 2023
Sample Complexity of Kernel-Based Q-Learning Sing-Yuan Yeh Fu-Chieh Chang Chang-Wei Yueh Pei-Yuan Wu A. Bernacchia Sattar Vakili OffRL 27 4 0 01 Feb 2023
Delayed Feedback in Kernel Bandits Sattar Vakili Danyal Ahmed A. Bernacchia Ciara Pike-Burke 11 6 0 01 Feb 2023
Uncertainty quantification for sparse spectral variational approximations in Gaussian process regression D. Nieman Botond Szabó Harry Van Zanten 31 5 0 21 Dec 2022
On Kernelized Multi-Armed Bandits with Constraints Xingyu Zhou Bo Ji 19 29 0 29 Mar 2022
Gaussian Process Bandit Optimization with Few Batches Zihan Li Jonathan Scarlett GP 131 47 0 15 Oct 2021
Contraction rates for sparse variational approximations in Gaussian process regression D. Nieman Botond Szabó Harry Van Zanten 52 17 0 22 Sep 2021
Connections and Equivalences between the Nyström Method and Sparse Variational Gaussian Processes Veit Wild Motonobu Kanagawa Dino Sejdinovic 38 16 0 02 Jun 2021
Regret Bounds for Noise-Free Kernel-Based Bandits Sattar Vakili 36 3 0 12 Feb 2020