This paper describes a framework for learning probabilistic models of objects and scenes and for exploiting these models for tracking complex, deformable, or articulated objects i...
There has been much interest in unsupervised learning of hierarchical generative models such as deep belief networks. Scaling such models to full-sized, high-dimensional images re...
Honglak Lee, Roger Grosse, Rajesh Ranganath, Andre...
Probabilistic data have recently become popular in applications such as scientific and geospatial databases. For images and other spatial datasets, probabilistic values can capture...
We present a sound and complete proof technique, based on syntactic logical relations, for showing contextual equivalence of expressions in a -calculus with recursive types and imp...
Relational database systems have been the dominating technology to manage and analyze large data warehouses. Moreover, the ER model, the standard in database design, has a close r...
Carlos Ordonez, Il-Yeol Song, Carlos Garcia-Alvara...