Fall 2020

Learning and Testing for Gradient Descent

Tuesday, December 15th, 2020 9:00 am9:30 am

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Emmanuel Abbe (EPFL)

We present lower-bounds for the generalization error of gradient descent on free initializations, reducing the problem to testing the algorithm’s output under different data models. We then discuss lower-bounds on random initialization and present the problem of learning communities in the pruned-block-model, where it is conjectured that GD fails.