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cs.LG2026
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…
cs.LG2026
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…
cs.LG2024
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…