269 citations · 3k across the 82 of their papers we have counts for
12 papers · 1 filter
Explicit Group Sparse Projection with Applications to Deep Learning and NMF
Riyasat Ohib, Nicolas Gillis, Niccolò Dalmasso +3
We design a new sparse projection method for a set of vectors that guarantees a desired average sparsity level measured leveraging the popular Hoyer measure (an affine function of…
Near-Convex Archetypal Analysis
Pierre De Handschutter, Nicolas Gillis, Arnaud Vandaele +1
Nonnegative matrix factorization (NMF) is a widely used linear dimensionality reduction technique for nonnegative data. NMF requires that each data point is approximated by a conve…
Successive Projection Algorithm Robust to Outliers
Nicolas Gillis
The successive projection algorithm (SPA) is a fast algorithm to tackle separable nonnegative matrix factorization (NMF). Given a nonnegative data matrix , SPA identifies an ind…
Multi-block Bregman proximal alternating linearized minimization and its application to orthogonal nonnegative matrix factorization
Masoud Ahookhosh, Le Thi Khanh Hien, Nicolas Gillis +1
We introduce and analyze BPALM and A-BPALM, two multi-block proximal alternating linearized minimization algorithms using Bregman distances for solving structured nonconvex problem…
Minimal-norm static feedbacks using dissipative Hamiltonian matrices
Nicolas Gillis, Punit Sharma
In this paper, we characterize the set of static-state feedbacks that stabilize a given continuous linear-time invariant system pair using dissipative Hamiltonian matrices. This ch…
Blind Audio Source Separation with Minimum-Volume Beta-Divergence NMF
Valentin Leplat, Nicolas Gillis, Man Shun Ang
Considering a mixed signal composed of various audio sources and recorded with a single microphone, we consider on this paper the blind audio source separation problem which consis…
A Provably Correct and Robust Algorithm for Convolutive Nonnegative Matrix Factorization
Anthony Degleris, Nicolas Gillis
In this paper, we propose a provably correct algorithm for convolutive nonnegative matrix factorization (CNMF) under separability assumptions. CNMF is a convolutive variant of nonn…
Generalized Separable Nonnegative Matrix Factorization
Junjun Pan, Nicolas Gillis
Nonnegative matrix factorization (NMF) is a linear dimensionality technique for nonnegative data with applications such as image analysis, text mining, audio source separation and…
Algorithms and Comparisons of Non-negative Matrix Factorization with Volume Regularization for Hyperspectral Unmixing
M. S. Ang, Nicolas Gillis
In this work, we consider nonnegative matrix factorization (NMF) with a regularization that promotes small volume of the convex hull spanned by the basis matrix. We present highly…
Inertial Block Proximal Methods for Non-Convex Non-Smooth Optimization
Le Thi Khanh Hien, Nicolas Gillis, Panagiotis Patrinos
We propose inertial versions of block coordinate descent methods for solving non-convex non-smooth composite optimization problems. Our methods possess three main advantages compar…
On approximating the nearest Ω-stable matrix
Neelam Choudhary, Nicolas Gillis, Punit Sharma
In this paper, we consider the problem of approximating a given matrix with a matrix whose eigenvalues lie in some specific region Ω, within the complex plane. More precisely, we c…
Distributionally Robust and Multi-Objective Nonnegative Matrix Factorization
Nicolas Gillis, Le Thi Khanh Hien, Valentin Leplat +1
Nonnegative matrix factorization (NMF) is a linear dimensionality reduction technique for analyzing nonnegative data. A key aspect of NMF is the choice of the objective function th…