In this paper, following the Compressed Sensing (CS) paradigm, we study the problem of recovering sparse or compressible signals from uniformly quantized measurements. We present ...
We address the problem of computing joint sparse representation of visual signal across multiple kernel-based representations. Such a problem arises naturally in supervised visual...
Abstract. Sparse signal models learned from data are widely used in audio, image, and video restoration. They have recently been generalized to discriminative image understanding t...
Julien Mairal, Marius Leordeanu, Francis Bach, Mar...
This work focuses on several optimization problems involved in recovery of sparse solutions of linear inverse problems. Such problems appear in many fields including image and sig...
We propose a new method for imaging sound speed in breast tissue from measurements obtained by ultrasound tomography (UST) scanners. Given the measurements, our algorithm finds a...
Ivana Tosic, Ivana Jovanovic, Pascal Frossard, Mar...