Exact Sparse Nonnegative Least Squares - Archive ouverte HAL Access content directly
Conference Papers Year : 2020

Exact Sparse Nonnegative Least Squares


We propose a novel approach to solve exactly the sparse nonnega-tive least squares problem, under hard 0 sparsity constraints. This approach is based on a dedicated branch-and-bound algorithm. This simple strategy is able to compute the optimal solution even in complicated cases such as noisy or ill-conditioned data, where traditional approaches fail. We also show that our algorithm scales well, despite the combinatorial nature of the problem. We illustrate the advantages of the proposed technique on synthetic data sets, as well as a real-world hyperspectral image.
Fichier principal
Vignette du fichier
version2.pdf (899.76 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-02634895 , version 1 (27-05-2020)



Nicolas Nadisic, Arnaud Vandaele, Nicolas Gillis, Jérémy E Cohen. Exact Sparse Nonnegative Least Squares. ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing, May 2020, Barcelona, France. pp.5395-5399, ⟨10.1109/ICASSP40776.2020.9053295⟩. ⟨hal-02634895⟩
46 View
476 Download



Gmail Facebook X LinkedIn More