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cs.LG2026
Regularity-Aware Stochastic MGDA with Adaptive Per-Iterate Conflict-Avoidant Update
Chentong Huang, Lisha Chen
Multi-objective learning (MOL) aims to optimize multiple objectives simultaneously. The multi-gradient descent algorithm (MGDA) constructs a common descent or conflict-avoidant (CA…
math.OC2026
Improved Convergence Rates for Stochastic Multi-Gradient Descent which Close the Gap: A Proof by AI
Lisha Chen
For smooth nonconvex stochastic multi-objective optimization, stochastic multi-gradient descent (SMG) computes an approximate steepest common descent direction of the objectives fr…
cs.LG2026
SURF: Steering the Scalarization Weight to Uniformly Traverse the Pareto Front
Liuyuan Jiang, Chentong Huang, Lisha Chen
Scalarization is widely used in multi-objective optimization owing to its simplicity and scalability. In many applications, the goal is to generate solutions that represent diverse…