PMF-CL derives Pareto-minimal-forgetting algorithms for linear/basis-function regression and quadratic-bounded losses like logistic regression, achieving static O(d²) memory for d-parameter models.
It is deeply rooted in cognitive science, as the ability to consolidate new information without overwriting existing knowledge is a hallmark of human intelligence (French, 1999)
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