4 papers
Few-for-Many Best-Arm Identification in Multi-Objective Bandits
Bo Xue, Yilu Liu, Haodong Jing +3
Real-world systems often serve many objectives but can deploy only a few options, whose performance must be learned from noisy feedback. Modeling each option as an arm in a multi-o…
Quality-Diversity Optimization as Multi-Objective Optimization
Xi Lin, Ping Guo, Yilu Liu +2
The Quality-Diversity (QD) optimization aims to discover a collection of high-performing solutions that simultaneously exhibit diverse behaviors within a user-defined behavior spac…
EoH-S: Evolution of Heuristic Set using LLMs for Automated Heuristic Design
Fei Liu, Yilu Liu, Qingfu Zhang +2
Automated Heuristic Design (AHD) using Large Language Models (LLMs) has achieved notable success in recent years. Despite the effectiveness of existing approaches, they only design…
Few for Many: Tchebycheff Set Scalarization for Many-Objective Optimization
Xi Lin, Yilu Liu, Xiaoyuan Zhang +3
Multi-objective optimization can be found in many real-world applications where some conflicting objectives can not be optimized by a single solution. Existing optimization methods…