2024 Poster "bayesian optimization" Papers
17 papers found
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.
Efficient Black-box Adversarial Attacks via Bayesian Optimization Guided by a Function Prior
Shuyu Cheng, Yibo Miao, Yinpeng Dong et al.
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.
Noise-Adaptive Confidence Sets for Linear Bandits and Application to Bayesian Optimization
Kwang-Sung Jun, Jungtaek Kim
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