We consider a generalization of the PDB homomorphism abstractions to what is called "structural patterns". The bais in abstracting the problem in hand into provably trac...
Approximate MAP inference in graphical models is an important and challenging problem for many domains including computer vision, computational biology and natural language unders...
An important theoretical tool in machine learning is the bias/variance decomposition of the generalization error. It was introduced for the mean square error in [3]. The bias/vari...
In this paper, we re-visit an original concept of speech coding in which the signal is separated into the carrier modulated by the signal envelope. A recently developed technique, ...
Abstract. This paper proposes an analysis technique for wide-band audio applications based on the predictability of the temporal evolution of Quadrature Mirror Filter (QMF) sub-ban...