13 citations · 23 across the 6 of their papers we have counts for
6 papers
On-the-fly spectral unmixing based on Kalman filtering
Hugues Kouakou, José Henrique de Morais Goulart, Raffaele Vitale +4
This work introduces an on-the-fly (i.e., online) linear unmixing method which is able to sequentially analyze spectral data acquired on a spectrum-by-spectrum basis. After derivin…
On the Accuracy of Hotelling-Type Asymmetric Tensor Deflation: A Random Tensor Analysis
Mohamed El Amine Seddik, Maxime Guillaud, Alexis Decurninge +1
This work introduces an asymptotic study of Hotelling-type tensor deflation in the presence of noise, in the regime of large tensor dimensions. Specifically, we consider a low-rank…
Majorization-minimization for Sparse Nonnegative Matrix Factorization with the -divergence
Arthur Marmin, José Henrique de Morais Goulart, Cédric Févotte
This article introduces new multiplicative updates for nonnegative matrix factorization with the -divergence and sparse regularization of one of the two factors (say, the activa…
COL0RME: Super-resolution microscopy based on sparse blinking/fluctuating fluorophore localization and intensity estimation
Vasiliki Stergiopoulou, Luca Calatroni, José Henrique de Morais Goulart +2
To overcome the physical barriers caused by light diffraction, super-resolution techniques are often applied in fluorescence microscopy. State-of-the-art approaches require specifi…
A Random Matrix Perspective on Random Tensors
José Henrique de Morais Goulart, Romain Couillet, Pierre Comon
Tensor models play an increasingly prominent role in many fields, notably in machine learning. In several applications, such as community detection, topic modeling and Gaussian mix…
Joint Majorization-Minimization for Nonnegative Matrix Factorization with the -divergence
Arthur Marmin, José Henrique de Morais Goulart, Cédric Févotte
This article proposes new multiplicative updates for nonnegative matrix factorization (NMF) with the -divergence objective function. Our new updates are derived from a joint maj…