PMF-CL derives Pareto-optimal solutions for continual learning on conflicting tasks, yielding memory-efficient algorithms for linear regression and quadratically bounded losses with static O(d^2) memory.
Federated learning meets multi-objective optimization
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PMF-CL: Pareto-Minimal-Forgetting Continual Learner for Conflicting Tasks
PMF-CL derives Pareto-optimal solutions for continual learning on conflicting tasks, yielding memory-efficient algorithms for linear regression and quadratically bounded losses with static O(d^2) memory.