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Regularity-Aware Stochastic MGDA with Adaptive Per-Iterate Conflict-Avoidant Update
Multi-objective learning (MOL) aims to optimize multiple objectives simultaneously. The multi-gradient descent algorithm (MGDA) constructs a common descent or conflict-avoidant (CA) direction by solving a gradient-aggregation subproblem. In stochastic settings, the vanilla stochastic MGDA method, SM
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