3 papers
cs.LG2026
Diversity-Driven Offline Multi-Objective Optimization via Nested Pareto Set Learning
Yiyi Zhu, Yaolin Wen, Xiang Xia +6
Multi-objective optimization (MOO) has emerged as a powerful approach to solving complex optimization problems involving multiple objectives. In many practical scenarios, function…
cs.LG2026
Automated Random Embedding for Practical Bayesian Optimization with Unknown Effective Dimension
Hong Qian, Xiang Shu, Xiang Xia +5
Bayesian optimization is widely employed for optimizing complex black-box functions but struggles with the curse of dimensionality. Random embedding, as a dimension reduction strat…
cs.AI2025
LLMOPT: Learning to Define and Solve General Optimization Problems from Scratch
Caigao Jiang, Xiang Shu, Hong Qian +4
Optimization problems are prevalent across various scenarios. Formulating and then solving optimization problems described by natural language often requires highly specialized hum…