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Warm Starting Bayesian Optimization

Warm Starting Bayesian Optimization

11 August 2016
Matthias Poloczek
Jialei Wang
P. Frazier
ArXiv (abs)PDFHTML

Papers citing "Warm Starting Bayesian Optimization"

31 / 31 papers shown
Title
Why risk matters for protein binder design
Why risk matters for protein binder design
Tudor-Stefan Cotet
Igor Krawczuk
114
0
0
31 Mar 2025
Language-Based Bayesian Optimization Research Assistant (BORA)
A. Cissé
Xenophon Evangelopoulos
V. Gusev
Andrew I. Cooper
139
1
0
28 Jan 2025
Sequential Large Language Model-Based Hyper-parameter Optimization
Sequential Large Language Model-Based Hyper-parameter Optimization
Kanan Mahammadli
Seyda Ertekin
238
5
0
27 Oct 2024
Robust Transfer Learning for Active Level Set Estimation with Locally
  Adaptive Gaussian Process Prior
Robust Transfer Learning for Active Level Set Estimation with Locally Adaptive Gaussian Process Prior
Giang Ngo
Dang Nguyen
Sunil Gupta
54
0
0
08 Oct 2024
Improving Hyperparameter Optimization with Checkpointed Model Weights
Improving Hyperparameter Optimization with Checkpointed Model Weights
Nikhil Mehta
Jonathan Lorraine
Steve Masson
Ramanathan Arunachalam
Zaid Pervaiz Bhat
James Lucas
Arun George Zachariah
107
4
0
26 Jun 2024
Reinforced In-Context Black-Box Optimization
Reinforced In-Context Black-Box Optimization
Lei Song
Chenxiao Gao
Ke Xue
Chenyang Wu
Dong Li
Haifeng Zhang
Zongzhang Zhang
Chao Qian
104
4
0
27 Feb 2024
Large Language Models to Enhance Bayesian Optimization
Large Language Models to Enhance Bayesian Optimization
Tennison Liu
Nicolás Astorga
Nabeel Seedat
M. Schaar
156
59
0
06 Feb 2024
Transfer Learning for Bayesian Optimization: A Survey
Transfer Learning for Bayesian Optimization: A Survey
Tianyi Bai
Yang Li
Yu Shen
Xinyi Zhang
Wentao Zhang
Tengjiao Wang
BDL
78
31
0
12 Feb 2023
Pre-training helps Bayesian optimization too
Pre-training helps Bayesian optimization too
Zehao Wang
George E. Dahl
Kevin Swersky
Chansoo Lee
Zelda E. Mariet
Zachary Nado
Justin Gilmer
Jasper Snoek
Zoubin Ghahramani
70
9
0
07 Jul 2022
On Provably Robust Meta-Bayesian Optimization
On Provably Robust Meta-Bayesian Optimization
Zhongxiang Dai
Yizhou Chen
Haibin Yu
K. H. Low
Patrick Jaillet
AAML
65
10
0
14 Jun 2022
Towards Learning Universal Hyperparameter Optimizers with Transformers
Towards Learning Universal Hyperparameter Optimizers with Transformers
Yutian Chen
Xingyou Song
Chansoo Lee
Zehao Wang
Qiuyi Zhang
...
Greg Kochanski
Arnaud Doucet
MarcÁurelio Ranzato
Sagi Perel
Nando de Freitas
105
65
0
26 May 2022
Pre-trained Gaussian processes for Bayesian optimization
Pre-trained Gaussian processes for Bayesian optimization
Zehao Wang
George E. Dahl
Kevin Swersky
Chansoo Lee
Zachary Nado
Justin Gilmer
Jasper Snoek
Zoubin Ghahramani
151
46
0
16 Sep 2021
Amortized Auto-Tuning: Cost-Efficient Bayesian Transfer Optimization for
  Hyperparameter Recommendation
Amortized Auto-Tuning: Cost-Efficient Bayesian Transfer Optimization for Hyperparameter Recommendation
Yuxin Xiao
Eric P. Xing
Willie Neiswanger
95
5
0
17 Jun 2021
JUMBO: Scalable Multi-task Bayesian Optimization using Offline Data
JUMBO: Scalable Multi-task Bayesian Optimization using Offline Data
Kourosh Hakhamaneshi
Pieter Abbeel
Vladimir M. Stojanović
Aditya Grover
74
10
0
02 Jun 2021
Warm Starting CMA-ES for Hyperparameter Optimization
Warm Starting CMA-ES for Hyperparameter Optimization
Masahiro Nomura
Shuhei Watanabe
Youhei Akimoto
Yoshihiko Ozaki
Masaki Onishi
93
43
0
13 Dec 2020
Scalable Bayesian Optimization with Sparse Gaussian Process Models
Scalable Bayesian Optimization with Sparse Gaussian Process Models
Ang Yang
50
0
0
26 Oct 2020
Automatic Tuning of Stochastic Gradient Descent with Bayesian
  Optimisation
Automatic Tuning of Stochastic Gradient Descent with Bayesian Optimisation
Victor Picheny
Vincent Dutordoir
A. Artemev
N. Durrande
50
2
0
25 Jun 2020
Interpretable Neural Architecture Search via Bayesian Optimisation with
  Weisfeiler-Lehman Kernels
Interpretable Neural Architecture Search via Bayesian Optimisation with Weisfeiler-Lehman Kernels
Binxin Ru
Xingchen Wan
Xiaowen Dong
Michael A. Osborne
86
22
0
13 Jun 2020
Neural Architecture Generator Optimization
Neural Architecture Generator Optimization
Binxin Ru
P. Esperança
Fabio Maria Carlucci
86
40
0
03 Apr 2020
On Hyper-parameter Tuning for Stochastic Optimization Algorithms
Haotian Zhang
Jianyong Sun
Zongben Xu
60
0
0
04 Mar 2020
Incorporating Expert Prior Knowledge into Experimental Design via
  Posterior Sampling
Incorporating Expert Prior Knowledge into Experimental Design via Posterior Sampling
Cheng Li
Sunil R. Gupta
Santu Rana
Vu Nguyen
A. Robles-Kelly
Svetha Venkatesh
106
15
0
26 Feb 2020
Practical Bayesian Optimization of Objectives with Conditioning
  Variables
Practical Bayesian Optimization of Objectives with Conditioning Variables
Michael Pearce
Janis Klaise
Matthew J. Groves
70
1
0
23 Feb 2020
A Quantile-based Approach for Hyperparameter Transfer Learning
A Quantile-based Approach for Hyperparameter Transfer Learning
David Salinas
Huibin Shen
Valerio Perrone
54
3
0
30 Sep 2019
Learning search spaces for Bayesian optimization: Another view of
  hyperparameter transfer learning
Learning search spaces for Bayesian optimization: Another view of hyperparameter transfer learning
Valerio Perrone
Huibin Shen
Matthias Seeger
Cédric Archambeau
Rodolphe Jenatton
75
97
0
27 Sep 2019
Efficient Transfer Bayesian Optimization with Auxiliary Information
Efficient Transfer Bayesian Optimization with Auxiliary Information
Tomoharu Iwata
Takuma Otsuka
69
2
0
17 Sep 2019
Bayesian Optimization for Policy Search via Online-Offline
  Experimentation
Bayesian Optimization for Policy Search via Online-Offline Experimentation
Benjamin Letham
E. Bakshy
OffRL
97
56
0
01 Apr 2019
Regret bounds for meta Bayesian optimization with an unknown Gaussian
  process prior
Regret bounds for meta Bayesian optimization with an unknown Gaussian process prior
Zi Wang
Beomjoon Kim
L. Kaelbling
77
54
0
23 Nov 2018
Hyperparameter Learning via Distributional Transfer
Hyperparameter Learning via Distributional Transfer
H. Law
P. Zhao
Lucian Chan
Junzhou Huang
Dino Sejdinovic
85
25
0
15 Oct 2018
BOHB: Robust and Efficient Hyperparameter Optimization at Scale
BOHB: Robust and Efficient Hyperparameter Optimization at Scale
Stefan Falkner
Aaron Klein
Frank Hutter
BDL
242
1,102
0
04 Jul 2018
Practical Transfer Learning for Bayesian Optimization
Practical Transfer Learning for Bayesian Optimization
Matthias Feurer
Benjamin Letham
Frank Hutter
E. Bakshy
142
35
0
06 Feb 2018
Multi-Information Source Optimization
Multi-Information Source Optimization
Matthias Poloczek
Jialei Wang
P. Frazier
104
198
0
01 Mar 2016
1