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High-Dimensional Bayesian Optimization with Sparse Axis-Aligned
  Subspaces

High-Dimensional Bayesian Optimization with Sparse Axis-Aligned Subspaces

27 February 2021
David Eriksson
M. Jankowiak
ArXivPDFHTML

Papers citing "High-Dimensional Bayesian Optimization with Sparse Axis-Aligned Subspaces"

26 / 26 papers shown
Title
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
59
0
0
18 Feb 2025
Exploiting Heterogeneity in Timescales for Sparse Recurrent Spiking
  Neural Networks for Energy-Efficient Edge Computing
Exploiting Heterogeneity in Timescales for Sparse Recurrent Spiking Neural Networks for Energy-Efficient Edge Computing
Biswadeep Chakraborty
Saibal Mukhopadhyay
36
2
0
08 Jul 2024
CATBench: A Compiler Autotuning Benchmarking Suite for Black-box Optimization
CATBench: A Compiler Autotuning Benchmarking Suite for Black-box Optimization
Jacob O. Tørring
Carl Hvarfner
Luigi Nardi
Magnus Sjalander
57
0
0
24 Jun 2024
A survey and benchmark of high-dimensional Bayesian optimization of
  discrete sequences
A survey and benchmark of high-dimensional Bayesian optimization of discrete sequences
Miguel González Duque
Richard Michael
Simon Bartels
Yevgen Zainchkovskyy
Søren Hauberg
Wouter Boomsma
42
4
0
07 Jun 2024
Personalized LLM Response Generation with Parameterized Memory Injection
Personalized LLM Response Generation with Parameterized Memory Injection
Kai Zhang
Lizhi Qing
Yangyang Kang
36
11
0
04 Apr 2024
Vanilla Bayesian Optimization Performs Great in High Dimensions
Vanilla Bayesian Optimization Performs Great in High Dimensions
Carl Hvarfner
E. Hellsten
Luigi Nardi
32
17
0
03 Feb 2024
A Bayesian approach for prompt optimization in pre-trained language
  models
A Bayesian approach for prompt optimization in pre-trained language models
Antonio Sabbatella
Andrea Ponti
Antonio Candelieri
I. Giordani
F. Archetti
23
1
0
01 Dec 2023
High-Dimensional Bayesian Optimization via Semi-Supervised Learning with
  Optimized Unlabeled Data Sampling
High-Dimensional Bayesian Optimization via Semi-Supervised Learning with Optimized Unlabeled Data Sampling
Y. Yin
Yu Wang
Gang Xu
24
4
0
04 May 2023
Network Cascade Vulnerability using Constrained Bayesian Optimization
Network Cascade Vulnerability using Constrained Bayesian Optimization
Albert Y. S. Lam
M. Anitescu
A. Subramanyam
14
0
0
27 Apr 2023
Increasing the Scope as You Learn: Adaptive Bayesian Optimization in
  Nested Subspaces
Increasing the Scope as You Learn: Adaptive Bayesian Optimization in Nested Subspaces
Leonard Papenmeier
Luigi Nardi
Matthias Poloczek
14
36
0
22 Apr 2023
Rotation Invariant Quantization for Model Compression
Rotation Invariant Quantization for Model Compression
Dor-Joseph Kampeas
Yury Nahshan
Hanoch Kremer
Gil Lederman
Shira Zaloshinski
Zheng Li
E. Haleva
MQ
18
0
0
03 Mar 2023
AutoPEFT: Automatic Configuration Search for Parameter-Efficient
  Fine-Tuning
AutoPEFT: Automatic Configuration Search for Parameter-Efficient Fine-Tuning
Han Zhou
Xingchen Wan
Ivan Vulić
Anna Korhonen
18
45
0
28 Jan 2023
Automatic and effective discovery of quantum kernels
Automatic and effective discovery of quantum kernels
Massimiliano Incudini
Daniele Lizzio Bosco
F. Martini
Michele Grossi
Giuseppe Serra
Alessandra Di Pierro
31
4
0
22 Sep 2022
Heterogeneous Recurrent Spiking Neural Network for Spatio-Temporal
  Classification
Heterogeneous Recurrent Spiking Neural Network for Spatio-Temporal Classification
Biswadeep Chakraborty
Saibal Mukhopadhyay
21
20
0
22 Sep 2022
Bayesian Optimization with Informative Covariance
Bayesian Optimization with Informative Covariance
Afonso Eduardo
Michael U. Gutmann
24
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
30
18
0
19 Jul 2022
Recent Advances in Bayesian Optimization
Recent Advances in Bayesian Optimization
Xilu Wang
Yaochu Jin
Sebastian Schmitt
Markus Olhofer
38
198
0
07 Jun 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
25
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
25
6
0
19 May 2022
A model aggregation approach for high-dimensional large-scale
  optimization
A model aggregation approach for high-dimensional large-scale optimization
Haowei Wang
Ercong Zhang
S. Ng
Giulia Pedrielli
22
1
0
16 May 2022
MolGenSurvey: A Systematic Survey in Machine Learning Models for
  Molecule Design
MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Design
Yuanqi Du
Tianfan Fu
Jimeng Sun
Shengchao Liu
AI4CE
31
86
0
28 Mar 2022
Sparse Bayesian Optimization
Sparse Bayesian Optimization
Sulin Liu
Qing Feng
David Eriksson
Benjamin Letham
E. Bakshy
27
7
0
03 Mar 2022
Local Latent Space Bayesian Optimization over Structured Inputs
Local Latent Space Bayesian Optimization over Structured Inputs
N. Maus
Haydn Jones
Juston Moore
Matt J. Kusner
John Bradshaw
J. Gardner
BDL
51
69
0
28 Jan 2022
LassoBench: A High-Dimensional Hyperparameter Optimization Benchmark
  Suite for Lasso
LassoBench: A High-Dimensional Hyperparameter Optimization Benchmark Suite for Lasso
Kenan Sehic
Alexandre Gramfort
Joseph Salmon
Luigi Nardi
22
35
0
04 Nov 2021
Multi-Objective Bayesian Optimization over High-Dimensional Search
  Spaces
Multi-Objective Bayesian Optimization over High-Dimensional Search Spaces
Sam Daulton
David Eriksson
Maximilian Balandat
E. Bakshy
20
105
0
22 Sep 2021
Re-Examining Linear Embeddings for High-Dimensional Bayesian
  Optimization
Re-Examining Linear Embeddings for High-Dimensional Bayesian Optimization
Benjamin Letham
Roberto Calandra
Akshara Rai
E. Bakshy
73
109
0
31 Jan 2020
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