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Gaussian Process Optimization with Adaptive Sketching: Scalable and No Regret
13 March 2019
Daniele Calandriello
Luigi Carratino
A. Lazaric
Michal Valko
Lorenzo Rosasco
GP
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Papers citing
"Gaussian Process Optimization with Adaptive Sketching: Scalable and No Regret"
10 / 10 papers shown
Title
Bayesian Optimization by Kernel Regression and Density-based Exploration
Tansheng Zhu
Hongyu Zhou
Ke Jin
Xusheng Xu
Qiufan Yuan
Lijie Ji
445
0
0
10 Feb 2025
An Online Learning Approach to Prompt-based Selection of Generative Models and LLMs
Xiaoyan Hu
Ho-fung Leung
Farzan Farnia
256
3
0
17 Oct 2024
Kernel Methods for Cooperative Multi-Agent Contextual Bandits
Abhimanyu Dubey
Alex Pentland
125
29
0
14 Aug 2020
Statistical and Computational Trade-Offs in Kernel K-Means
Daniele Calandriello
Lorenzo Rosasco
51
32
0
27 Aug 2019
When Gaussian Process Meets Big Data: A Review of Scalable GPs
Haitao Liu
Yew-Soon Ong
Xiaobo Shen
Jianfei Cai
GP
115
695
0
03 Jul 2018
Batched Large-scale Bayesian Optimization in High-dimensional Spaces
Zi Wang
Clement Gehring
Pushmeet Kohli
Stefanie Jegelka
UQCV
73
216
0
05 Jun 2017
On Kernelized Multi-armed Bandits
Sayak Ray Chowdhury
Aditya Gopalan
127
463
0
03 Apr 2017
An Introduction to Matrix Concentration Inequalities
J. Tropp
178
1,155
0
07 Jan 2015
Finite-Time Analysis of Kernelised Contextual Bandits
Michal Valko
N. Korda
Rémi Munos
I. Flaounas
N. Cristianini
196
275
0
26 Sep 2013
Practical Bayesian Optimization of Machine Learning Algorithms
Jasper Snoek
Hugo Larochelle
Ryan P. Adams
384
7,981
0
13 Jun 2012
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