activity
20152021
most citedDifferentially Private Sliced Wasserstein Distance

4 citations · 8 across the 5 of their papers we have counts for

collaborators

8 papers

cs.LG20214 cited

Differentially Private Sliced Wasserstein Distance

Alain Rakotomamonjy, Liva Ralaivola

Developing machine learning methods that are privacy preserving is today a central topic of research, with huge practical impacts. Among the numerous ways to address privacy-preser…

cs.LG20201 cited

Partial Trace Regression and Low-Rank Kraus Decomposition

Hachem Kadri, Stéphane Ayache, Riikka Huusari +2

The trace regression model, a direct extension of the well-studied linear regression model, allows one to map matrices to real-valued outputs. We here introduce an even more genera…

cs.LG2020

Quantum Bandits

Balthazar Casalé, Giuseppe Di Molfetta, Hachem Kadri +1

We consider the quantum version of the bandit problem known as {\em best arm identification} (BAI). We first propose a quantum modeling of the BAI problem, which assumes that both…

cs.LG2019

QuicK-means: Acceleration of K-means by learning a fast transform

Luc Giffon, Valentin Emiya, Liva Ralaivola +1

K-means -- and the celebrated Lloyd algorithm -- is more than the clustering method it was originally designed to be. It has indeed proven pivotal to help increase the speed of man…

math.OC2019

Recovery and convergence rate of the Frank-Wolfe Algorithm for the m-EXACT-SPARSE Problem

Farah Cherfaoui, Valentin Emiya, Liva Ralaivola +1

We study the properties of the Frank-Wolfe algorithm to solve the m-EXACT-SPARSE reconstruction problem, where a signal y must be expressed as a sparse linear combination of a pred…

cs.LG2018

Frank-Wolfe Algorithm for the Exact Sparse Problem

Farah Cherfaoui, Valentin Emiya, Liva Ralaivola +1

In this paper, we study the properties of the Frank-Wolfe algorithm to solve the \ExactSparse reconstruction problem. We prove that when the dictionary is quasi-incoherent, at each…