ICML "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 2024posterarXiv:2402.07692
Conformal Validity Guarantees Exist for Any Data Distribution (and How to Find Them)
Drew Prinster, Samuel Stanton, Anqi Liu et al.
ICML 2024posterarXiv:2405.06627
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 2024posterarXiv:2405.03547
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