ICML 2024 "black-box optimization" Papers
8 papers found
Boundary Exploration for Bayesian Optimization With Unknown Physical Constraints
Yunsheng Tian, Ane Zuniga, Xinwei Zhang et al.
ICML 2024poster
Conformal Validity Guarantees Exist for Any Data Distribution (and How to Find Them)
Drew Prinster, Samuel Stanton, Anqi Liu et al.
ICML 2024poster
FedBPT: Efficient Federated Black-box Prompt Tuning for Large Language Models
Jingwei Sun, Ziyue Xu, Hongxu Yin et al.
ICML 2024poster
MALIBO: Meta-learning for Likelihood-free Bayesian Optimization
Jiarong Pan, Stefan Falkner, Felix Berkenkamp et al.
ICML 2024spotlight
Offline Multi-Objective Optimization
Ke Xue, Rong-Xi Tan, Xiaobin Huang et al.
ICML 2024poster
Position: Leverage Foundational Models for Black-Box Optimization
Xingyou Song, Yingtao Tian, Robert Lange et al.
ICML 2024poster
Towards AutoAI: Optimizing a Machine Learning System with Black-box and Differentiable Components
Zhiliang Chen, Chuan-Sheng Foo, Bryan Kian Hsiang Low
ICML 2024poster
Use Your INSTINCT: INSTruction optimization for LLMs usIng Neural bandits Coupled with Transformers
Xiaoqiang Lin, Zhaoxuan Wu, Zhongxiang Dai et al.
ICML 2024poster