Random linear network codes can be designed and implemented in a distributed manner, with low computational complexity. However, these codes are classically implemented [1] over fi...
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...
Despite its ubiquitous presence, very little is known about the odds of winning the simple card game of Klondike Solitaire. The main goal of this paper is to investigate the use o...
We propose a new family of probabilistic description logics (DLs) that, in contrast to most existing approaches, are derived in a principled way from Halpern’s probabilistic fi...
There are two broad approaches to query evaluation over probabilistic databases: (1) Intensional Methods proceed by manipulating expressions over symbolic events associated with u...