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ZHENG Wenjie

PhD graduated
Team : MLIA
Departure date : 12/25/2018

Supervision : Patrick GALLINARI

A Distributed Frank–Wolfe Framework for Trace Norm Minimization via the Bulk Synchronous Parallel Model

Learning low-rank matrices is a problem of great importance in statistics, machine learning, computer vision, recommender systems, etc. Because of its NP-hard nature, a principled approach is to solve its tightest convex relaxation: trace norm minimization. Among various algorithms capable of solving this optimization is the Frank-Wolfe method, which is particularly suitable for high-dimensional matrices. In preparation for the usage of distributed infrastructures to further accelerate the computation, this study aims at exploring the possibility of executing the Frank-Wolfe algorithm in a star network with the Bulk Synchronous Parallel (BSP) model and investigating its efficiency both theoretically and empirically.

Defence : 06/13/2018 - 14h00 - Site Jussieu 24-25/101

Jury members :

Taïani François, Professeur [Rapporteur]
Amini Massih-Reza, Professeur [Rapporteur]
Naacke Hubert, Maître de conférences
Bellet Aurélien, Chargé de Recherches
Germain Cécile, Professeur
Denoyer Ludovic, Professeur
Gallinari Patrick, Professeur

2017-2018 Publications

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