24/11/17 – Emilie Chouzenoux

Orateur: Emilie Chouzenoux (CVN, CentraleSupélec/INRIA, Université Paris-Est, Marne-La-Vallée)
Titre: A Random Block – Coordinate Douglas – Rach Splitting Method with low Computational Complexity for Binary Logistic Regression

In this talk, I will present a new optimization algorithm for sparse logistic regression based on a stochastic version of the Douglas-Rachford splitting method. The algorithm sweeps the training set by randomly selecting a mini-batch of data at each iteration, and it allows us to update the variables in a block coordinate manner. Our approach leverages the proximity operator of the logistic loss, which is expressed with the generalized Lambert W function. Experiments carried out on standard datasets demonstrate the efficiency of our approach w.r.t. stochastic gradient-like methods. (joint work with Luis M. Briceño-Arias, Afef Cherni, Giovanni Chierchia and Jean-Christophe Pesquet)

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