Jean Lafond

2 accepted papers

2017

Fast and privacy preserving distributed low-rank regression

Hoi-To Wai, Anna Scaglione, Jean Lafond, Eric Moulines

ICASSP 2017accepted

This paper proposes a fast and privacy preserving distributed algorithm for handling low-rank regression problems with nuclear norm constraint. Traditional projected gradient algorithms have high computation costs due to their projection steps when they are used to solve these problems. Our gossip-b…

Cited by 0 Source ↗Scholar ↗

2016

D-FW: Communication efficient distributed algorithms for high-dimensional sparse optimization

Jean Lafond, Hoi-To Wai, Eric Moulines

ICASSP 2016accepted

We propose distributed algorithms for high-dimensional sparse optimization. In many applications, the parameter is sparse but high-dimensional. This is pathological for existing distributed algorithms as the latter require an information exchange stage involving transmission of the full parameter, w…

Cited by 0 Source ↗Scholar ↗