Memorias de investigación
Ponencias en congresos:
Cross-Products LASSO
Año:2013
Áreas de investigación
  • Inferencia lineal, regresión,
  • Trastornos cardiovasculares
Datos
Descripción
Negative co-occurrence is a common phenomenon in many signal processing applications. In some cases the signals involved are sparse, and this information can be exploited to recover them. In this paper, we present a sparse learning approach that explicitly takes into account negative co-occurrence. This is achieved by adding a novel penalty term to the LASSO cost function based on the cross-products between the reconstruction coefficients. Although the resulting optimization problem is non-convex, we develop a new and efficient method for solving it based on successive convex approximations. Results on synthetic data, for both complete and overcomplete dictionaries, are provided to validate the proposed approach.
Internacional
Si
Nombre congreso
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
Tipo de participación
960
Lugar del congreso
Vancouver (Canadá)
Revisores
Si
ISBN o ISSN
978-1-4799-0356-6
DOI
Fecha inicio congreso
26/05/2013
Fecha fin congreso
31/05/2013
Desde la página
6118
Hasta la página
6122
Título de las actas
Proceedings of the 2013 IEEE International Conference on Acoustics, Speech, and Signal Processing
Esta actividad pertenece a memorias de investigación
Participantes
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Departamento: Ingeniería de Circuitos y Sistemas