ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2001.11659
  4. Cited By
Re-Examining Linear Embeddings for High-Dimensional Bayesian
  Optimization

Re-Examining Linear Embeddings for High-Dimensional Bayesian Optimization

31 January 2020
Benjamin Letham
Roberto Calandra
Akshara Rai
E. Bakshy
ArXivPDFHTML

Papers citing "Re-Examining Linear Embeddings for High-Dimensional Bayesian Optimization"

12 / 12 papers shown
Title
Learning Low-Dimensional Embeddings for Black-Box Optimization
Learning Low-Dimensional Embeddings for Black-Box Optimization
Riccardo Busetto
Manas Mejari
Marco Forgione
Alberto Bemporad
Dario Piga
10
0
0
02 May 2025
Pushing the Limits of the Reactive Affine Shaker Algorithm to Higher Dimensions
Pushing the Limits of the Reactive Affine Shaker Algorithm to Higher Dimensions
R. Battiti
M. Brunato
49
0
0
18 Feb 2025
Expected Coordinate Improvement for High-Dimensional Bayesian Optimization
Expected Coordinate Improvement for High-Dimensional Bayesian Optimization
Dawei Zhan
32
5
0
18 Apr 2024
Learning Regions of Interest for Bayesian Optimization with Adaptive
  Level-Set Estimation
Learning Regions of Interest for Bayesian Optimization with Adaptive Level-Set Estimation
Fengxue Zhang
Jialin Song
James Bowden
Alexander Ladd
Yisong Yue
Thomas A. Desautels
Yuxin Chen
25
6
0
25 Jul 2023
Gradient-Free Textual Inversion
Gradient-Free Textual Inversion
Zhengcong Fei
Mingyuan Fan
Junshi Huang
DiffM
13
31
0
12 Apr 2023
Falsification of Cyber-Physical Systems using Bayesian Optimization
Falsification of Cyber-Physical Systems using Bayesian Optimization
Zahra Ramezani
Kenan Sehic
Luigi Nardi
K. Åkesson
19
1
0
14 Sep 2022
Bayesian Optimization with Informative Covariance
Bayesian Optimization with Informative Covariance
Afonso Eduardo
Michael U. Gutmann
11
3
0
04 Aug 2022
Investigating Bayesian optimization for expensive-to-evaluate black box
  functions: Application in fluid dynamics
Investigating Bayesian optimization for expensive-to-evaluate black box functions: Application in fluid dynamics
Mike Diessner
Joseph O’Connor
A. Wynn
S. Laizet
Yu Guan
Kevin J. Wilson
Richard D. Whalley
25
18
0
19 Jul 2022
Sample-Efficient Optimisation with Probabilistic Transformer Surrogates
Sample-Efficient Optimisation with Probabilistic Transformer Surrogates
A. Maraval
Matthieu Zimmer
Antoine Grosnit
Rasul Tutunov
Jun Wang
H. Ammar
17
2
0
27 May 2022
ODBO: Bayesian Optimization with Search Space Prescreening for Directed
  Protein Evolution
ODBO: Bayesian Optimization with Search Space Prescreening for Directed Protein Evolution
Lixue Cheng
Ziyi Yang
Chang-Yu Hsieh
Ben Liao
Shengyu Zhang
19
6
0
19 May 2022
Black-Box Tuning for Language-Model-as-a-Service
Black-Box Tuning for Language-Model-as-a-Service
Tianxiang Sun
Yunfan Shao
Hong Qian
Xuanjing Huang
Xipeng Qiu
VLM
24
254
0
10 Jan 2022
Variable noise and dimensionality reduction for sparse Gaussian
  processes
Variable noise and dimensionality reduction for sparse Gaussian processes
Edward Snelson
Zoubin Ghahramani
75
74
0
27 Jun 2012
1