High Dimensional Bayesian Optimization with Kernel Principal Component
Analysis

High Dimensional Bayesian Optimization with Kernel Principal Component Analysis

28 April 2022

Papers citing "High Dimensional Bayesian Optimization with Kernel Principal Component Analysis"

11 / 11 papers shown

Title
High Dimensional Bayesian Optimization Assisted by Principal Component Analysis Elena Raponi Hao Wang M. Bujny S. Boria Carola Doerr 43 31 0 02 Jul 2020
A kernel Principal Component Analysis (kPCA) digest with a new backward mapping (pre-image reconstruction) strategy Alberto García-González A. Huerta S. Zlotnik Pedro Díez 27 14 0 07 Jan 2020
Randomly Projected Additive Gaussian Processes for Regression Ian A. Delbridge D. Bindel A. Wilson 45 27 0 30 Dec 2019
High-Dimensional Bayesian Optimization via Additive Models with Overlapping Groups Paul Rolland Jonathan Scarlett Ilija Bogunovic Volkan Cevher 61 115 0 20 Feb 2018
High Dimensional Bayesian Optimization Using Dropout Cheng Li Sunil R. Gupta Santu Rana Vu Nguyen Svetha Venkatesh A. Shilton 45 130 0 15 Feb 2018
COCO: A Platform for Comparing Continuous Optimizers in a Black-Box Setting N. Hansen A. Auger Raymond Ros Olaf Mersmann Tea Tušar D. Brockhoff 55 424 0 29 Mar 2016
Bayesian Optimization with Dimension Scheduling: Application to Biological Systems Doniyor Ulmasov C. Baroukh Benoît Chachuat M. Deisenroth Ruth Misener 56 40 0 17 Nov 2015
On ANOVA decompositions of kernels and Gaussian random field paths D. Ginsbourger O. Roustant Dominic Schuhmacher N. Durrande Nicolas Lenz 54 26 0 21 Sep 2014
Bayesian Optimization in a Billion Dimensions via Random Embeddings Ziyun Wang Frank Hutter M. Zoghi David Matheson Nando de Freitas 161 443 0 09 Jan 2013
Additive Gaussian Processes David Duvenaud H. Nickisch C. Rasmussen GP 94 329 0 19 Dec 2011
Convergence rates of efficient global optimization algorithms Adam D. Bull 114 641 0 18 Jan 2011