6 papers
Computing Lower Bounds on the Nonnegative Rank via Non-Convex Optimization Solvers
Timothy Baeckelant, Arnaud Vandaele, Nicolas Gillis
The nonnegative rank of a nonnegative matrix is the smallest number of nonnegative rank-one factors that sum to . Since computing the nonnegative rank is NP-hard, it is comm…
Supervised Deep Multimodal Matrix Factorization for Interpretable Brain Network Analysis
Amjad Seyedi, Lifang He, Songlin Zhao +2
We present Supervised Deep Multimodal Matrix Factorization (SD3MF), an interpretable framework for integrative brain network analysis that generalizes Symmetric Nonnegative Matrix…
Matrix Factorization Framework for Community Detection under the Degree-Corrected Block Model
Alexandra Dache, Arnaud Vandaele, Nicolas Gillis
Community detection is a fundamental task in data analysis, and block models provide an approach for identifying a wide variety of community structures while offering high interpre…
Nonnegative Matrix Factorization in the Component-Wise L1 Norm for Sparse Data
Giovanni Seraghiti, Kévin Dubrulle, Arnaud Vandaele +1
Nonnegative matrix factorization (NMF) approximates a nonnegative matrix, , by the product of two nonnegative factors, , where has columns and has rows. In t…
Algorithms for Boolean Matrix Factorization using Integer Programming and Heuristics
Christos Kolomvakis, Thomas Bobille, Arnaud Vandaele +1
Boolean matrix factorization (BMF) approximates a given binary input matrix as the product of two smaller binary factors. Unlike binary matrix factorization based on standard arith…
Efficient algorithms for the Hadamard decomposition
Samuel Wertz, Arnaud Vandaele, Nicolas Gillis
The Hadamard decomposition is a powerful technique for data analysis and matrix compression, which decomposes a given matrix into the element-wise product of two or more low-rank m…