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stat.ML2020
Risk bounds when learning infinitely many response functions by ordinary linear regression
Vincent Plassier, François Portier, Johan Segers
Consider the problem of learning a large number of response functions simultaneously based on the same input variables. The training data consist of a single independent random sam…
math.ST2020★ 1 cited
Asymptotic Analysis of Conditioned Stochastic Gradient Descent
Rémi Leluc, François Portier
In this paper, we investigate a general class of stochastic gradient descent (SGD) algorithms, called Conditioned SGD, based on a preconditioning of the gradient direction. Using a…