High-Dimensional Bayesian Optimization with Sparse Axis-Aligned Subspaces

27 February 2021

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

29 / 29 papers shown

Title
Pushing the Limits of the Reactive Affine Shaker Algorithm to Higher Dimensions R. Battiti M. Brunato 64 0 0 18 Feb 2025
Exploiting Heterogeneity in Timescales for Sparse Recurrent Spiking Neural Networks for Energy-Efficient Edge Computing Biswadeep Chakraborty Saibal Mukhopadhyay 38 2 0 08 Jul 2024
CATBench: A Compiler Autotuning Benchmarking Suite for Black-box Optimization Jacob O. Tørring Carl Hvarfner Luigi Nardi Magnus Sjalander 63 0 0 24 Jun 2024
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 44 4 0 07 Jun 2024
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 Carl Hvarfner E. Hellsten Luigi Nardi 32 17 0 03 Feb 2024
Improving sample efficiency of high dimensional Bayesian optimization with MCMC Zeji Yi Yunyue Wei Chu Xin Cheng Kaibo He Yanan Sui 22 5 0 05 Jan 2024
A Bayesian approach for prompt optimization in pre-trained language models Antonio Sabbatella Andrea Ponti Antonio Candelieri I. Giordani Francesco Archetti 34 1 0 01 Dec 2023
RTDK-BO: High Dimensional Bayesian Optimization with Reinforced Transformer Deep kernels Alexander Shmakov Avisek Naug Vineet Gundecha Sahand Ghorbanpour Ricardo Luna Gutierrez Ashwin Ramesh Babu Antonio Guillen-Perez Soumyendu Sarkar 29 11 0 05 Oct 2023
High-Dimensional Bayesian Optimization via Semi-Supervised Learning with Optimized Unlabeled Data Sampling Y. Yin Yu Wang Gang Xu 32 4 0 04 May 2023
Network Cascade Vulnerability using Constrained Bayesian Optimization Albert Y. S. Lam M. Anitescu A. Subramanyam 22 0 0 27 Apr 2023
Increasing the Scope as You Learn: Adaptive Bayesian Optimization in Nested Subspaces Leonard Papenmeier Luigi Nardi Matthias Poloczek 21 36 0 22 Apr 2023
Rotation Invariant Quantization for Model Compression Dor-Joseph Kampeas Yury Nahshan Hanoch Kremer Gil Lederman Shira Zaloshinski Zheng Li E. Haleva MQ 23 0 0 03 Mar 2023
AutoPEFT: Automatic Configuration Search for Parameter-Efficient Fine-Tuning Han Zhou Xingchen Wan Ivan Vulić Anna Korhonen 24 45 0 28 Jan 2023
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 Biswadeep Chakraborty Saibal Mukhopadhyay 31 20 0 22 Sep 2022
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 Mike Diessner Joseph O’Connor A. Wynn S. Laizet Yu Guan Kevin J. Wilson Richard D. Whalley 36 18 0 19 Jul 2022
Recent Advances in Bayesian Optimization Xilu Wang Yaochu Jin Sebastian Schmitt Markus Olhofer 38 200 0 07 Jun 2022
Sample-Efficient Optimisation with Probabilistic Transformer Surrogates A. Maraval Matthieu Zimmer Antoine Grosnit Rasul Tutunov Jun Wang H. Ammar 30 2 0 27 May 2022
ODBO: Bayesian Optimization with Search Space Prescreening for Directed Protein Evolution Lixue Cheng Ziyi Yang Chang-Yu Hsieh Ben Liao Shengyu Zhang 27 6 0 19 May 2022
A model aggregation approach for high-dimensional large-scale optimization Haowei Wang Ercong Zhang Szu Hui Ng Giulia Pedrielli 22 1 0 16 May 2022
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 Sulin Liu Qing Feng David Eriksson Benjamin Letham E. Bakshy 30 7 0 03 Mar 2022
Scalable Bayesian Optimization Using Vecchia Approximations of Gaussian Processes Felix Jimenez Matthias Katzfuss 21 10 0 02 Mar 2022
Local Latent Space Bayesian Optimization over Structured Inputs Natalie Maus Haydn Thomas Jones Juston Moore Matt J. Kusner John Bradshaw Jacob R. Gardner BDL 55 69 0 28 Jan 2022
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 Sam Daulton David Eriksson Maximilian Balandat E. Bakshy 22 105 0 22 Sep 2021
Re-Examining Linear Embeddings for High-Dimensional Bayesian Optimization Benjamin Letham Roberto Calandra Akshara Rai E. Bakshy 75 110 0 31 Jan 2020