We present a new approximate inference algorithm for Deep Boltzmann Machines (DBM's), a generative model with many layers of hidden variables. The algorithm learns a separate...
This paper presents an unsupervised learning algorithm that can derive the probabilistic dependence structure of parts of an object (a moving human body in our examples) automatic...
Learning graphical models with hidden variables can offer semantic insights to complex data and lead to salient structured predictors without relying on expensive, sometime unatta...
Robust data retrieval in the presence of uncertainty is a challenging problem in multimedia information retrieval. In query-by-humming (QBH) systems, uncertainty can arise in query...
Erdem Unal, Elaine Chew, Panayiotis G. Georgiou, S...
We develop a method for the estimation of articulated pose, such as that of the human body or the human hand, from a single (monocular) image. Pose estimation is formulated as a s...