ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1807.02811
  4. Cited By
A Tutorial on Bayesian Optimization

A Tutorial on Bayesian Optimization

8 July 2018
P. Frazier
    GP
ArXiv (abs)PDFHTML

Papers citing "A Tutorial on Bayesian Optimization"

50 / 721 papers shown
Model-Based Diffusion for Trajectory Optimization
Model-Based Diffusion for Trajectory Optimization
Chaoyi Pan
Zeji Yi
Guanya Shi
Guannan Qu
265
35
0
28 May 2024
BO4IO: A Bayesian optimization approach to inverse optimization with
  uncertainty quantification
BO4IO: A Bayesian optimization approach to inverse optimization with uncertainty quantification
Yen-An Lu
Wei-Shou Hu
J. Paulson
Qi Zhang
151
3
0
28 May 2024
AI-Assisted Detector Design for the EIC (AID(2)E)
AI-Assisted Detector Design for the EIC (AID(2)E)
M. Diefenthaler
C. Fanelli
L. Gerlach
Wen Guan
Tanja Horn
...
C. Pecar
Karthik Suresh
Anselm Vossen
T. Wang
T. Wenaus
200
4
0
25 May 2024
Minimizing UCB: a Better Local Search Strategy in Local Bayesian
  Optimization
Minimizing UCB: a Better Local Search Strategy in Local Bayesian Optimization
Zheyi Fan
Wenyu Wang
Szu Hui Ng
Q. Hu
176
6
0
24 May 2024
Parameter Identification for Electrochemical Models of Lithium-Ion
  Batteries Using Bayesian Optimization
Parameter Identification for Electrochemical Models of Lithium-Ion Batteries Using Bayesian OptimizationIFAC-PapersOnLine (IFAC-PapersOnLine), 2024
Jianzong Pi
Samuel Filgueira da Silva
M. F. Ozkan
Abhishek Gupta
Marcello Canova
101
5
0
17 May 2024
CatCMA : Stochastic Optimization for Mixed-Category Problems
CatCMA : Stochastic Optimization for Mixed-Category ProblemsAnnual Conference on Genetic and Evolutionary Computation (GECCO), 2024
Ryoki Hamano
Shota Saito
Masahiro Nomura
Kento Uchida
Shinichi Shirakawa
375
9
0
16 May 2024
The DNA of Calabi-Yau Hypersurfaces
The DNA of Calabi-Yau Hypersurfaces
Nate MacFadden
Andreas Schachner
Elijah Sheridan
279
4
0
14 May 2024
CAGES: Cost-Aware Gradient Entropy Search for Efficient Local Multi-Fidelity Bayesian Optimization
CAGES: Cost-Aware Gradient Entropy Search for Efficient Local Multi-Fidelity Bayesian Optimization
Wei-Ting Tang
J. Paulson
261
3
0
13 May 2024
Outlier-robust Kalman Filtering through Generalised Bayes
Outlier-robust Kalman Filtering through Generalised BayesInternational Conference on Machine Learning (ICML), 2024
Gerardo Duran-Martín
Matias Altamirano
Alexander Y. Shestopaloff
Leandro Sánchez-Betancourt
Jeremias Knoblauch
Matt Jones
F. Briol
Kevin P. Murphy
342
25
0
09 May 2024
Dynamic Anisotropic Smoothing for Noisy Derivative-Free Optimization
Dynamic Anisotropic Smoothing for Noisy Derivative-Free OptimizationInternational Conference on Machine Learning (ICML), 2024
S. Reifenstein
T. Leleu
Yoshihisa Yamamoto
238
1
0
02 May 2024
Hyperparameter Optimization Can Even be Harmful in Off-Policy Learning
  and How to Deal with It
Hyperparameter Optimization Can Even be Harmful in Off-Policy Learning and How to Deal with It
Yuta Saito
Masahiro Nomura
OffRL
297
4
0
23 Apr 2024
Adaptive Catalyst Discovery Using Multicriteria Bayesian Optimization
  with Representation Learning
Adaptive Catalyst Discovery Using Multicriteria Bayesian Optimization with Representation Learning
Jie Chen
Pengfei Ou
Yuxin Chang
Hengrui Zhang
Xiao-Yan Li
E. H. Sargent
Wei Chen
130
4
0
18 Apr 2024
Expected Coordinate Improvement for High-Dimensional Bayesian Optimization
Expected Coordinate Improvement for High-Dimensional Bayesian Optimization
Dawei Zhan
274
13
0
18 Apr 2024
Bayesian Inference for Consistent Predictions in Overparameterized
  Nonlinear Regression
Bayesian Inference for Consistent Predictions in Overparameterized Nonlinear Regression
Tomoya Wakayama
BDL
307
0
0
06 Apr 2024
Demand Balancing in Primal-Dual Optimization for Blind Network Revenue
  Management
Demand Balancing in Primal-Dual Optimization for Blind Network Revenue Management
Sentao Miao
Yining Wang
181
0
0
06 Apr 2024
Navigating the Evaluation Funnel to Optimize Iteration Speed for
  Recommender Systems
Navigating the Evaluation Funnel to Optimize Iteration Speed for Recommender Systems
Claire Schultzberg
Brammert Ottens
OffRL
89
0
0
03 Apr 2024
An Optimization Framework to Personalize Passive Cardiac Mechanics
An Optimization Framework to Personalize Passive Cardiac MechanicsComputer Methods in Applied Mechanics and Engineering (CMAME), 2024
Lei Shi
Ian Chen
Hiroo Takayama
Vijay Vedula
250
9
0
03 Apr 2024
Checkpoint Merging via Bayesian Optimization in LLM Pretraining
Checkpoint Merging via Bayesian Optimization in LLM Pretraining
Deyuan Liu
Zecheng Wang
Bingning Wang
Weipeng Chen
Chunshan Li
Zhiying Tu
Dianhui Chu
Bo Li
Dianbo Sui
MoMe
291
26
0
28 Mar 2024
BLADE: Enhancing Black-box Large Language Models with Small
  Domain-Specific Models
BLADE: Enhancing Black-box Large Language Models with Small Domain-Specific Models
Haitao Li
Jiaxin Mao
Jia Chen
Qian Dong
Zhijing Wu
Yiqun Liu
Chong Chen
Qi Tian
AILaw
227
24
0
27 Mar 2024
Goal-Oriented Bayesian Optimal Experimental Design for Nonlinear Models using Markov Chain Monte Carlo
Goal-Oriented Bayesian Optimal Experimental Design for Nonlinear Models using Markov Chain Monte Carlo
Shijie Zhong
Wanggang Shen
Tommie A. Catanach
Xun Huan
202
9
0
26 Mar 2024
Multiple-Source Localization from a Single-Snapshot Observation Using
  Graph Bayesian Optimization
Multiple-Source Localization from a Single-Snapshot Observation Using Graph Bayesian Optimization
Zonghan Zhang
Zijian Zhang
Zhiqian Chen
117
3
0
25 Mar 2024
Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey
Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey
Zeyu Han
Chao Gao
Jinyang Liu
Jeff Zhang
Sai Qian Zhang
800
707
0
21 Mar 2024
Storm Surge Modeling in the AI ERA: Using LSTM-based Machine Learning
  for Enhancing Forecasting Accuracy
Storm Surge Modeling in the AI ERA: Using LSTM-based Machine Learning for Enhancing Forecasting Accuracy
S. Giaremis
Noujoud Nader
Clint Dawson
Hartmut Kaiser
Carola Kaiser
Efstratios Nikidis
102
20
0
07 Mar 2024
TS-RSR: A provably efficient approach for batch Bayesian Optimization
TS-RSR: A provably efficient approach for batch Bayesian Optimization
Tongzheng Ren
Na Li
411
2
0
07 Mar 2024
Sparse Spiking Neural Network: Exploiting Heterogeneity in Timescales
  for Pruning Recurrent SNN
Sparse Spiking Neural Network: Exploiting Heterogeneity in Timescales for Pruning Recurrent SNN
Biswadeep Chakraborty
Beomseok Kang
H. Kumar
Saibal Mukhopadhyay
325
17
0
06 Mar 2024
Bayesian Differentiable Physics for Cloth Digitalization
Bayesian Differentiable Physics for Cloth Digitalization
Deshan Gong
Ningtao Mao
He Wang
AI4CE
362
4
0
27 Feb 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
280
9
0
27 Feb 2024
Feedback Efficient Online Fine-Tuning of Diffusion Models
Feedback Efficient Online Fine-Tuning of Diffusion Models
Masatoshi Uehara
Yulai Zhao
Kevin Black
Ehsan Hajiramezanali
Gabriele Scalia
N. Diamant
Alex Tseng
Sergey Levine
Tommaso Biancalani
385
40
0
26 Feb 2024
Concurrent Learning of Policy and Unknown Safety Constraints in
  Reinforcement Learning
Concurrent Learning of Policy and Unknown Safety Constraints in Reinforcement Learning
Lunet Yifru
Ali Baheri
OffRL
226
1
0
24 Feb 2024
Beyond Simple Averaging: Improving NLP Ensemble Performance with Topological-Data-Analysis-Based Weighting
Beyond Simple Averaging: Improving NLP Ensemble Performance with Topological-Data-Analysis-Based Weighting
P. Proskura
Alexey Zaytsev
290
0
0
22 Feb 2024
MSTAR: Multi-Scale Backbone Architecture Search for Timeseries
  Classification
MSTAR: Multi-Scale Backbone Architecture Search for Timeseries Classification
Tue Cao
N.H. Tran
Hieu H. Pham
Hung T. Nguyen
Le P. Nguyen
198
1
0
21 Feb 2024
FlexHB: a More Efficient and Flexible Framework for Hyperparameter
  Optimization
FlexHB: a More Efficient and Flexible Framework for Hyperparameter Optimization
Yang Zhang
Haiyang Wu
Yuekui Yang
230
1
0
21 Feb 2024
Trust Regions for Explanations via Black-Box Probabilistic Certification
Trust Regions for Explanations via Black-Box Probabilistic Certification
Amit Dhurandhar
Swagatam Haldar
Dennis L. Wei
Karthikeyan N. Ramamurthy
FAtt
395
3
0
17 Feb 2024
Fixed Confidence Best Arm Identification in the Bayesian Setting
Fixed Confidence Best Arm Identification in the Bayesian Setting
Kyoungseok Jang
Junpei Komiyama
Kazutoshi Yamazaki
260
0
0
16 Feb 2024
Transition Constrained Bayesian Optimization via Markov Decision
  Processes
Transition Constrained Bayesian Optimization via Markov Decision Processes
Jose Pablo Folch
Calvin Tsay
Robert M. Lee
B. Shafei
Weronika Ormaniec
Andreas Krause
Mark van der Wilk
Ruth Misener
Mojmír Mutný
359
8
0
13 Feb 2024
Principled Preferential Bayesian Optimization
Principled Preferential Bayesian Optimization
Wenjie Xu
Wenbin Wang
Yuning Jiang
B. Svetozarevic
Colin N. Jones
279
12
0
08 Feb 2024
Voronoi Candidates for Bayesian Optimization
Voronoi Candidates for Bayesian Optimization
Nathan Wycoff
John W. Smith
Annie S. Booth
R. Gramacy
250
4
0
07 Feb 2024
Large Language Models to Enhance Bayesian Optimization
Large Language Models to Enhance Bayesian OptimizationInternational Conference on Learning Representations (ICLR), 2024
Tennison Liu
Nicolás Astorga
Nabeel Seedat
M. Schaar
403
112
0
06 Feb 2024
On the development of a practical Bayesian optimisation algorithm for
  expensive experiments and simulations with changing environmental conditions
On the development of a practical Bayesian optimisation algorithm for expensive experiments and simulations with changing environmental conditionsData-Centric Engineering (DCE), 2024
Mike Diessner
Kevin J. Wilson
Richard D. Whalley
186
2
0
05 Feb 2024
Accelerating Look-ahead in Bayesian Optimization: Multilevel Monte Carlo
  is All you Need
Accelerating Look-ahead in Bayesian Optimization: Multilevel Monte Carlo is All you Need
Shangda Yang
Vitaly Zankin
Maximilian Balandat
Stefan Scherer
Kevin Carlberg
Neil S. Walton
Kody J. H. Law
337
4
0
03 Feb 2024
GenFormer: A Deep-Learning-Based Approach for Generating Multivariate
  Stochastic Processes
GenFormer: A Deep-Learning-Based Approach for Generating Multivariate Stochastic Processes
Haoran Zhao
Wayne Isaac Tan Uy
AI4TS
87
0
0
03 Feb 2024
Simulation-based optimization of a production system topology -- a
  neural network-assisted genetic algorithm
Simulation-based optimization of a production system topology -- a neural network-assisted genetic algorithm
N. Paape
J. V. Eekelen
M. A. Reniers
57
0
0
02 Feb 2024
cmaes : A Simple yet Practical Python Library for CMA-ES
cmaes : A Simple yet Practical Python Library for CMA-ES
Masahiro Nomura
Masashi Shibata
313
42
0
02 Feb 2024
Enhancing Gaussian Process Surrogates for Optimization and Posterior
  Approximation via Random Exploration
Enhancing Gaussian Process Surrogates for Optimization and Posterior Approximation via Random Exploration
Hwanwoo Kim
D. Sanz-Alonso
320
6
0
30 Jan 2024
Bayesian optimization as a flexible and efficient design framework for
  sustainable process systems
Bayesian optimization as a flexible and efficient design framework for sustainable process systems
J. Paulson
Calvin Tsay
TPM
268
46
0
29 Jan 2024
Asymptotic properties of Vecchia approximation for Gaussian processes
Asymptotic properties of Vecchia approximation for Gaussian processes
Myeongjong Kang
Florian Schafer
J. Guinness
Matthias Katzfuss
256
8
0
29 Jan 2024
Integrating Human Expertise in Continuous Spaces: A Novel Interactive
  Bayesian Optimization Framework with Preference Expected Improvement
Integrating Human Expertise in Continuous Spaces: A Novel Interactive Bayesian Optimization Framework with Preference Expected Improvement
Nikolaus Feith
Elmar Rueckert
296
1
0
23 Jan 2024
A Unified Gaussian Process for Branching and Nested Hyperparameter
  Optimization
A Unified Gaussian Process for Branching and Nested Hyperparameter Optimization
Jiazhao Zhang
Ying Hung
Chung-Ching Lin
Zicheng Liu
281
0
0
19 Jan 2024
Learning-assisted Stochastic Capacity Expansion Planning: A Bayesian
  Optimization Approach
Learning-assisted Stochastic Capacity Expansion Planning: A Bayesian Optimization Approach
Aron Brenner
Rahman Khorramfar
D. Mallapragada
Saurabh Amin
182
1
0
19 Jan 2024
Simulation Based Bayesian Optimization
Simulation Based Bayesian Optimization
Roi Naveiro
Becky Tang
245
1
0
19 Jan 2024
Previous
123456...131415
Next