In this paper, we introduce a novel bayesian compressive sensing (CS) technique for phonetic classification. CS is often used to characterize a signal from a few support training...
Tara N. Sainath, Avishy Carmi, Dimitri Kanevsky, B...
In this paper we present a mixture density based approach to invariant image object recognition. We start our experiments using Gaussian mixture densities within a Bayesian classi...
, Yunde Jia Model structure selection is currently an open problem in modeling data via Gaussian Mixture Models (GMM). This paper proposes a discriminative method to select GMM st...
This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
Image attention is the basic technique for many computer vision applications. In this paper, we propose an adaptive Bayesian framework to detect the image attention in color image...