AI RESEARCH
Information-Theoretic Generalization Bounds for Stochastic Gradient Descent with Predictable Virtual Noise
arXiv CS.LG
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ArXi:2605.00064v1 Announce Type: new Information-theoretic generalization bounds analyze stochastic optimization by relating expected generalization error to the mutual information between learned parameters and