The development of accurate models and efficient algorithms for the analysis of multivariate categorical data are important and longstanding problems in machine learning and compu...
Mohammad Emtiyaz Khan, Shakir Mohamed, Benjamin M....
In this paper we describe a methodology for model-based single channel separation of sounds. We present a sparse latent variable model that can learn sounds based on their distribu...
Paris Smaragdis, Bhiksha Raj, Madhusudana V. S. Sh...
We introduce Gaussian process dynamical models (GPDMs) for nonlinear time series analysis, with applications to learning models of human pose and motion from high-dimensional motio...
We present a Bayesian search algorithm for learning the structure of latent variable models of continuous variables. We stress the importance of applying search operators designed...
We investigate genre effects on the task of automatic sentence segmentation, focusing on two important domains – broadcast news (BN) and broadcast conversation (BC). We employ a...