Detalle del congreso
Autores: Tianju Sui; Damián Marelli; Minyue Fu.
Resumen: Despite of its wide success in many distributedstatistical learning applications, the well-known Gaussian beliefpropagation (BP) algorithm still lacks sufficient understandingat the theoretical level. This paper studies the convergenceof Gaussian BP by analyzing the dynamic behaviour of themarginal covariances. We show, under a mild technical as-sumption, that the information matrices (i.e., the inverses ofmarginal covariances) are guaranteed to converge exponentiallyto positive-definite matrices. The convergence rate is explicitlycharacterized. This result is a key step to the understanding ofthe dynamic behaviour of the BP iterations.
Tipo de reunión: Conferencia.
Tipo de trabajo: Artículo Completo.
Producción: Convergence Analysis of Gaussian Belief Propagation: Dynamic Behaviour of Marginal Covariances.
Reunión científica: IEEE Conference on on Acoustics, Speech, and Signal Processing (ICASSP).
Lugar: Shanghai.
Institución organizadora: Institute of Electrical and Electronics Engineers (IEEE).
Publicado: Sí
Lugar publicación: Nueva York
Mes de reunión: 3
Año: 2016.