Dataflow programming has proven to be popular for representing applications in rapid prototyping tools for digital signal processing (DSP); however, existing dataflow design tools...
In this paper, we study the problem of learning in the presence of classification noise in the probabilistic learning model of Valiant and its variants. In order to identify the cl...
Patterns on real-world objects are often due to variations in geometry across the surface. Height fields and other common parametric methods cannot synthesize many forms of geomet...
Traditional Information Extraction (IE) takes a relation name and hand-tagged examples of that relation as input. Open IE is a relationindependent extraction paradigm that is tail...
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...