A Unified Framework for Gradient Aggregation in Multi-Objective Optimization 事件

A Unified Framework for Gradient Aggregation in Multi-Objective Optimization arXiv:2605.30452v1 Announce Type: cross Abstract: Many machine learning problems involve multiple inherent trade-offs that are best addressed by gradient-based multi-objective optimization (MOO) algorithms. Existing methods are often proposed with various motivations, analyzed case by case, and differ algorithmically in how the component gradients are aggregated at each step. In this work, we develop a unifying framewo