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arXiv · 1105.4701

Online Learning, Stability, and Stochastic Gradient Descent

Tomaso Poggio·Stephen Voinea·Lorenzo Rosasco
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Abstract

In batch learning, stability together with existence and uniqueness of the solution corresponds to well-posedness of Empirical Risk Minimization (ERM) methods; recently, it was proved that CV_loo stability is necessary and sufficient for generalization and consistency of ERM. In this note, we introduce CV_on stability, which plays a similar note in online learning. We show that stochastic gradient descent (SDG) with the usual hypotheses is CVon stable and we then discuss the implications of CV_on stability for convergence of SGD.

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Tomaso Poggio, Stephen Voinea, Lorenzo Rosasco. 2011-05-24. Online Learning, Stability, and Stochastic Gradient Descent. https://arxiv.org/abs/1105.4701

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