In high-dimensional continual linear regression, optimal fixed L2 regularization strength scales as T/ln T with the number of tasks and mitigates label noise for arbitrary linear teachers.
27 KARPELMOROSHKOLEVINSTEINMEIRSOUDRYEVRON Term 2: 2E tX k=2 St:k w⋆ k−1 −w ⋆ k + (w⋆ t −w ⋆ i ) !⊤ St:1 (w0 −w ⋆
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Optimal L2 Regularization in High-dimensional Continual Linear Regression
In high-dimensional continual linear regression, optimal fixed L2 regularization strength scales as T/ln T with the number of tasks and mitigates label noise for arbitrary linear teachers.