Papers
Communities
Events
Blog
Pricing
Search
Open menu
Home
Papers
1910.01739
Cited By
Scalable Global Optimization via Local Bayesian Optimization
3 October 2019
Samyam Rajbhandari
Michael Pearce
J. Gardner
Ryan D. Turner
Matthias Poloczek
Re-assign community
ArXiv
PDF
HTML
Papers citing
"Scalable Global Optimization via Local Bayesian Optimization"
50 / 233 papers shown
Title
Revisiting Architecture-aware Knowledge Distillation: Smaller Models and Faster Search
Taehyeon Kim
Heesoo Myeong
Se-Young Yun
21
2
0
27 Jun 2022
Scalable First-Order Bayesian Optimization via Structured Automatic Differentiation
Sebastian Ament
Carla P. Gomes
16
8
0
16 Jun 2022
Recent Advances in Bayesian Optimization
Xilu Wang
Yaochu Jin
Sebastian Schmitt
Markus Olhofer
38
197
0
07 Jun 2022
Relaxed Gaussian process interpolation: a goal-oriented approach to Bayesian optimization
S. Petit
Julien Bect
E. Vázquez
33
1
0
07 Jun 2022
ODBO: Bayesian Optimization with Search Space Prescreening for Directed Protein Evolution
Lixue Cheng
Ziyi Yang
Chang-Yu Hsieh
Ben Liao
Shengyu Zhang
25
6
0
19 May 2022
A model aggregation approach for high-dimensional large-scale optimization
Haowei Wang
Ercong Zhang
S. Ng
Giulia Pedrielli
14
1
0
16 May 2022
Self-focusing virtual screening with active design space pruning
David E. Graff
Matteo Aldeghi
Joseph A. Morrone
K. E. Jordan
Edward O. Pyzer-Knapp
Connor W. Coley
24
24
0
03 May 2022
Randomized Maximum Likelihood via High-Dimensional Bayesian Optimization
Valentin Breaz
Richard D. Wilkinson
19
0
0
17 Apr 2022
Auditing Privacy Defenses in Federated Learning via Generative Gradient Leakage
Zhuohang Li
Jiaxin Zhang
Lu Liu
Jian-Dong Liu
FedML
22
114
0
29 Mar 2022
LAMBDA: Covering the Solution Set of Black-Box Inequality by Search Space Quantization
Lihao Liu
Tianyue Feng
Xingyu Xing
Junyi Chen
11
1
0
25 Mar 2022
Accelerating Bayesian Optimization for Biological Sequence Design with Denoising Autoencoders
Samuel Stanton
Wesley J. Maddox
Nate Gruver
Phillip M. Maffettone
E. Delaney
Peyton Greenside
A. Wilson
BDL
31
89
0
23 Mar 2022
Learning Representation for Bayesian Optimization with Collision-free Regularization
Fengxue Zhang
Brian D. Nord
Yuxin Chen
OOD
BDL
9
2
0
16 Mar 2022
Sparse Bayesian Optimization
Sulin Liu
Qing Feng
David Eriksson
Benjamin Letham
E. Bakshy
25
7
0
03 Mar 2022
Scalable Bayesian Optimization Using Vecchia Approximations of Gaussian Processes
Felix Jimenez
Matthias Katzfuss
8
10
0
02 Mar 2022
Mold into a Graph: Efficient Bayesian Optimization over Mixed-Spaces
Jaeyeon Ahn
Taehyeon Kim
Seyoung Yun
24
0
0
02 Feb 2022
AntBO: Towards Real-World Automated Antibody Design with Combinatorial Bayesian Optimisation
M. A. Khan
Alexander I. Cowen-Rivers
Antoine Grosnit
Derrick-Goh-Xin Deik
Philippe A. Robert
...
Rasul Tutunov
Dany Bou-Ammar
Jun Wang
Amos Storkey
Haitham Bou-Ammar
45
22
0
29 Jan 2022
Local Latent Space Bayesian Optimization over Structured Inputs
N. Maus
Haydn Jones
Juston Moore
Matt J. Kusner
John Bradshaw
J. Gardner
BDL
49
69
0
28 Jan 2022
Predicting the utility of search spaces for black-box optimization: a simple, budget-aware approach
Setareh Ariafar
Justin Gilmer
Zachary Nado
Jasper Snoek
Rodolphe Jenatton
George E. Dahl
36
1
0
15 Dec 2021
Triangulation candidates for Bayesian optimization
R. Gramacy
Anna Sauer
Nathan Wycoff
8
13
0
14 Dec 2021
Two-step Lookahead Bayesian Optimization with Inequality Constraints
Yunxiang Zhang
X. Zhang
P. Frazier
14
7
0
06 Dec 2021
Efficient Calibration of Multi-Agent Simulation Models from Output Series with Bayesian Optimization
Yuanlu Bai
H. Lam
Svitlana Vyetrenko
T. Balch
20
10
0
03 Dec 2021
Optimizing High-Dimensional Physics Simulations via Composite Bayesian Optimization
Wesley J. Maddox
Qing Feng
Maximilian Balandat
17
7
0
29 Nov 2021
Searching in the Forest for Local Bayesian Optimization
Difan Deng
Marius Lindauer
25
2
0
10 Nov 2021
Approximate Neural Architecture Search via Operation Distribution Learning
Xingchen Wan
Binxin Ru
P. Esperança
Fabio Maria Carlucci
28
7
0
08 Nov 2021
LassoBench: A High-Dimensional Hyperparameter Optimization Benchmark Suite for Lasso
Kenan Sehic
Alexandre Gramfort
Joseph Salmon
Luigi Nardi
20
35
0
04 Nov 2021
Conditioning Sparse Variational Gaussian Processes for Online Decision-making
Wesley J. Maddox
Samuel Stanton
A. Wilson
17
28
0
28 Oct 2021
A machine learning approach for fighting the curse of dimensionality in global optimization
J. Schumann
Alejandro M. Aragón
13
2
0
28 Oct 2021
Differentially Private Federated Bayesian Optimization with Distributed Exploration
Zhongxiang Dai
K. H. Low
P. Jaillet
FedML
8
40
0
27 Oct 2021
A portfolio approach to massively parallel Bayesian optimization
M. Binois
Nicholson T. Collier
J. Ozik
11
9
0
18 Oct 2021
Machine Learning with Knowledge Constraints for Process Optimization of Open-Air Perovskite Solar Cell Manufacturing
Zhe Liu
Nicholas Rolston
Austin C. Flick
T. Colburn
Zekun Ren
R. Dauskardt
Tonio Buonassisi
19
116
0
01 Oct 2021
Learning Periodic Tasks from Human Demonstrations
Jingyun Yang
Junwu Zhang
Connor Settle
Akshara Rai
Rika Antonova
Jeannette Bohg
104
24
0
28 Sep 2021
Multi-Objective Bayesian Optimization over High-Dimensional Search Spaces
Sam Daulton
David Eriksson
Maximilian Balandat
E. Bakshy
20
105
0
22 Sep 2021
SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization
Marius Lindauer
Katharina Eggensperger
Matthias Feurer
André Biedenkapp
Difan Deng
C. Benjamins
Tim Ruhopf
René Sass
Frank Hutter
83
326
0
20 Sep 2021
Computationally Efficient High-Dimensional Bayesian Optimization via Variable Selection
Yi Shen
Carl Kingsford
42
8
0
20 Sep 2021
HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO
Katharina Eggensperger
Philip Muller
Neeratyoy Mallik
Matthias Feurer
René Sass
Aaron Klein
Noor H. Awad
Marius Lindauer
Frank Hutter
35
100
0
14 Sep 2021
Unsupervised Reservoir Computing for Solving Ordinary Differential Equations
M. Mattheakis
H. Joy
P. Protopapas
15
13
0
25 Aug 2021
Scalable3-BO: Big Data meets HPC - A scalable asynchronous parallel high-dimensional Bayesian optimization framework on supercomputers
Anh Tran
6
0
0
12 Aug 2021
Hyperparameter Optimization: Foundations, Algorithms, Best Practices and Open Challenges
B. Bischl
Martin Binder
Michel Lang
Tobias Pielok
Jakob Richter
...
Theresa Ullmann
Marc Becker
A. Boulesteix
Difan Deng
Marius Lindauer
79
448
0
13 Jul 2021
Scaling Gaussian Processes with Derivative Information Using Variational Inference
Misha Padidar
Xinran Zhu
Leo Huang
J. Gardner
D. Bindel
BDL
14
18
0
08 Jul 2021
Local policy search with Bayesian optimization
Sarah Müller
Alexander von Rohr
Sebastian Trimpe
BDL
13
38
0
22 Jun 2021
Learning Space Partitions for Path Planning
Kevin Kaichuang Yang
Tianjun Zhang
Chris Cummins
Brandon Cui
Benoit Steiner
Linnan Wang
Joseph E. Gonzalez
Dan Klein
Yuandong Tian
15
10
0
19 Jun 2021
ChaCha for Online AutoML
Qingyun Wu
Chi Wang
John Langford
Paul Mineiro
Marco Rossi
27
7
0
09 Jun 2021
High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning
Antoine Grosnit
Rasul Tutunov
A. Maraval
Ryan-Rhys Griffiths
Alexander I. Cowen-Rivers
...
Wenlong Lyu
Zhitang Chen
Jun Wang
Jan Peters
Haitham Bou-Ammar
BDL
DRL
16
58
0
07 Jun 2021
Bayesian Optimisation for Constrained Problems
Juan Ungredda
Juergen Branke
13
12
0
27 May 2021
Benchmarking the Performance of Bayesian Optimization across Multiple Experimental Materials Science Domains
Qiaohao Liang
Aldair E. Gongora
Zekun Ren
A. Tiihonen
Zhe Liu
...
K. Hippalgaonkar
Benji Maruyama
Keith A. Brown
John W Fisher Iii
Tonio Buonassisi
19
118
0
23 May 2021
Bag of Baselines for Multi-objective Joint Neural Architecture Search and Hyperparameter Optimization
Julia Guerrero-Viu
Sven Hauns
Sergio Izquierdo
Guilherme Miotto
Simon Schrodi
André Biedenkapp
T. Elsken
Difan Deng
Marius Lindauer
Frank Hutter
AI4CE
17
25
0
03 May 2021
Deep Learning for Bayesian Optimization of Scientific Problems with High-Dimensional Structure
Samuel Kim
Peter Y. Lu
Charlotte Loh
Jamie Smith
Jasper Snoek
M. Soljavcić
BDL
AI4CE
63
17
0
23 Apr 2021
Bayesian Optimization is Superior to Random Search for Machine Learning Hyperparameter Tuning: Analysis of the Black-Box Optimization Challenge 2020
Ryan Turner
David Eriksson
M. McCourt
J. Kiili
Eero Laaksonen
Zhen Xu
Isabelle M Guyon
BDL
16
288
0
20 Apr 2021
Bayesian Algorithm Execution: Estimating Computable Properties of Black-box Functions Using Mutual Information
W. Neiswanger
Ke Alexander Wang
Stefano Ermon
MLAU
21
30
0
19 Apr 2021
Automatic Termination for Hyperparameter Optimization
Anastasia Makarova
Huibin Shen
Valerio Perrone
Aaron Klein
Jean Baptiste Faddoul
Andreas Krause
Matthias Seeger
Cédric Archambeau
22
22
0
16 Apr 2021
Previous
1
2
3
4
5
Next