5 papers
On The Linear Convergence of Bregman Proximal Gradient Methods with Applications to Kullback--Leibler regression
Jonathan Chirinos-RodrÃguez, Christian Daniele, Cédric Févotte +1
Bregman Proximal Gradient methods (BPGM) exploit the underlying geometry of the objective function through a carefully chosen mirror map. In this work, we introduce a novel notion…
Enhancing time-frequency resolution with optimal transport and barycentric fusion of multiple spectrogram
David Valdivia, Elsa Cazelles, Cédric Févotte
Time-frequency representations, such as the short-time Fourier transform (STFT), are fundamental tools for analyzing non-stationary signals. However, their ability to achieve sharp…
Optimization landscape of -Bregman relaxations
Jonathan Chirinos-RodrÃguez, Cédric Févotte, Emmanuel Soubies
In this paper, we study (noisy) linear systems, and their -regularized optimization problems, coupled with general data fidelity terms. Recent approaches for solving this c…
Whitening Spherical Gaussian Mixtures in the Large-Dimensional Regime
Mohammed Racim Moussa Boudjemaa, Alper Kalle, Xiaoyi Mai +2
Whitening is a classical technique in unsupervised learning that can facilitate estimation tasks by standardizing data. An important application is the estimation of latent variabl…
PDRs4All XX. Haute Couture: Spectral stitching of JWST MIRI-IFU cubes with matrix completion
Amélie Canin, Cédric Févotte, Nicolas Dobigeon +3
MIRI is the imager and spectrograph covering wavelengths from to m onboard the James Webb Space Telescope (JWST). The Medium-Resolution Spectrometer (MRS) consists…