6 citations · 7 across the 3 of their papers we have counts for
3 papers
Smoothed Separable Nonnegative Matrix Factorization
Nicolas Nadisic, Nicolas Gillis, Christophe Kervazo
Given a set of data points belonging to the convex hull of a set of vertices, a key problem in linear algebra, signal processing, data analysis and machine learning is to estimate…
Matrix-wise -constrained Sparse Nonnegative Least Squares
Nicolas Nadisic, Jeremy E Cohen, Arnaud Vandaele +1
Nonnegative least squares problems with multiple right-hand sides (MNNLS) arise in models that rely on additive linear combinations. In particular, they are at the core of most non…
Sparse Separable Nonnegative Matrix Factorization
Nicolas Nadisic, Arnaud Vandaele, Jeremy E. Cohen +1
We propose a new variant of nonnegative matrix factorization (NMF), combining separability and sparsity assumptions. Separability requires that the columns of the first NMF factor…