"bayesian optimization" Papers

Bayesian Optimization with Preference Exploration using a Monotonic Neural Network Ensemble

Hanyang Wang, Juergen Branke, Matthias Poloczek

Causal Discovery via Bayesian Optimization

Bao Duong, Sunil Gupta, Thin Nguyen

Informed Initialization for Bayesian Optimization and Active Learning

Carl Hvarfner, David Eriksson, Eytan Bakshy et al.

Robust and Computation-Aware Gaussian Processes

Accelerating Look-ahead in Bayesian Optimization: Multilevel Monte Carlo is All you Need

Shangda Yang, Vitaly Zankin, Maximilian Balandat et al.

A Sober Look at LLMs for Material Discovery: Are They Actually Good for Bayesian Optimization Over Molecules?

Agustinus Kristiadi, Felix Strieth-Kalthoff, Marta Skreta et al.

Bayesian Optimization of Function Networks with Partial Evaluations

Poompol Buathong, Jiayue Wan, Raul Astudillo et al.

Boundary Exploration for Bayesian Optimization With Unknown Physical Constraints

Yunsheng Tian, Ane Zuniga, Xinwei Zhang et al.

Constrained Bayesian Optimization under Partial Observations: Balanced Improvements and Provable Convergence

Shengbo Wang, Ke Li

Domain Invariant Learning for Gaussian Processes and Bayesian Exploration

Xilong Zhao, Siyuan Bian, Yaoyun Zhang et al.

Efficient Black-box Adversarial Attacks via Bayesian Optimization Guided by a Function Prior

Shuyu Cheng, Yibo Miao, Yinpeng Dong et al.

High-Dimensional Bayesian Optimization via Semi-Supervised Learning with Optimized Unlabeled Data Sampling

Yuxuan Yin, Yu Wang, Peng Li

In-Context Freeze-Thaw Bayesian Optimization for Hyperparameter Optimization

Herilalaina Rakotoarison, Steven Adriaensen, Neeratyoy Mallik et al.

InstructZero: Efficient Instruction Optimization for Black-Box Large Language Models

Lichang Chen, Jiuhai Chen, Tom Goldstein et al.

Joint Composite Latent Space Bayesian Optimization

Natalie Maus, Zhiyuan Jerry Lin, Maximilian Balandat et al.

Kernelized Normalizing Constant Estimation: Bridging Bayesian Quadrature and Bayesian Optimization

Xu Cai, Jonathan Scarlett

MALIBO: Meta-learning for Likelihood-free Bayesian Optimization

Jiarong Pan, Stefan Falkner, Felix Berkenkamp et al.

Multi-Objective Bayesian Optimization with Active Preference Learning

Ryota Ozaki, Kazuki Ishikawa, Youhei Kanzaki et al.

Noise-Adaptive Confidence Sets for Linear Bandits and Application to Bayesian Optimization

Kwang-Sung Jun, Jungtaek Kim

Pareto Front-Diverse Batch Multi-Objective Bayesian Optimization

Alaleh Ahmadianshalchi, Syrine Belakaria, Janardhan Rao Doppa

Posterior Sampling-Based Bayesian Optimization with Tighter Bayesian Regret Bounds

Shion Takeno, Yu Inatsu, Masayuki Karasuyama et al.

Probability Distribution of Hypervolume Improvement in Bi-objective Bayesian Optimization

Hao Wang, Kaifeng Yang, Michael Affenzeller

Quality-Weighted Vendi Scores And Their Application To Diverse Experimental Design

Quan Nguyen, Adji Bousso Dieng

Random Exploration in Bayesian Optimization: Order-Optimal Regret and Computational Efficiency

Sudeep Salgia, Sattar Vakili, Qing Zhao

Safe Exploration in Dose Finding Clinical Trials with Heterogeneous Participants

Isabel Chien, Wessel Bruinsma, Javier Gonzalez et al.

Towards AutoAI: Optimizing a Machine Learning System with Black-box and Differentiable Components

Zhiliang Chen, Chuan-Sheng Foo, Bryan Kian Hsiang Low

Use Your INSTINCT: INSTruction optimization for LLMs usIng Neural bandits Coupled with Transformers

Xiaoqiang Lin, Zhaoxuan Wu, Zhongxiang Dai et al.

Vanilla Bayesian Optimization Performs Great in High Dimensions

Carl Hvarfner, Erik Hellsten, Luigi Nardi