735 citations · 871 across the 27 of their papers we have counts for
6 papers · 1 filter
Learning efficient sparse and low rank models
Pablo Sprechmann, Alex M. Bronstein, Guillermo Sapiro
Parsimony, including sparsity and low rank, has been shown to successfully model data in numerous machine learning and signal processing tasks. Traditionally, such modeling approac…
Computer vision tools for the non-invasive assessment of autism-related behavioral markers
Jordan Hashemi, Thiago Vallin Spina, Mariano Tepper +4
The early detection of developmental disorders is key to child outcome, allowing interventions to be initiated that promote development and improve prognosis. Research on autism sp…
Sparse Modeling of Intrinsic Correspondences
J. Pokrass, A. M. Bronstein, M. M. Bronstein +2
We present a novel sparse modeling approach to non-rigid shape matching using only the ability to detect repeatable regions. As the input to our algorithm, we are given only two se…
A Complete System for Candidate Polyps Detection in Virtual Colonoscopy
Marcelo Fiori, Pablo Musé, Guillermo Sapiro
Computer tomographic colonography, combined with computer-aided detection, is a promising emerging technique for colonic polyp analysis. We present a complete pipeline for polyp de…
Learning Robust Low-Rank Representations
Pablo Sprechmann, Alex M. Bronstein, Guillermo Sapiro
In this paper we present a comprehensive framework for learning robust low-rank representations by combining and extending recent ideas for learning fast sparse coding regressors w…
Are You Imitating Me? Unsupervised Sparse Modeling for Group Activity Analysis from a Single Video
Zhongwei Tang, Alexey Castrodad, Mariano Tepper +1
A framework for unsupervised group activity analysis from a single video is here presented. Our working hypothesis is that human actions lie on a union of low-dimensional subspaces…