3 papers
cs.LG2026
Adaptive Online Mirror Descent for Tchebycheff Scalarization in Multi-Objective Learning
Meitong Liu, Xiaoyuan Zhang, Chulin Xie +2
Multi-objective learning (MOL) aims to learn under multiple potentially conflicting objectives and strike a proper balance. While recent preference-guided MOL methods often rely on…
cs.LG2025
Gradient-Based Multi-Objective Deep Learning: Algorithms, Theories, Applications, and Beyond
Weiyu Chen, Baijiong Lin, Xiaoyuan Zhang +4
Many modern deep learning applications require balancing multiple objectives that are often conflicting. Examples include multi-task learning, fairness-aware learning, and the alig…
cs.MS2024
LibMOON: A Gradient-based MultiObjective OptimizatioN Library in PyTorch
Xiaoyuan Zhang, Liang Zhao, Yingying Yu +4
Multiobjective optimization problems (MOPs) are prevalent in machine learning, with applications in multi-task learning, learning under fairness or robustness constraints, etc. Ins…