Abstract. We propose a verification method for parameterized systems with global conditions. The method is based on context-sensitive constraints, a symbolic representation of infi...
Parosh Aziz Abdulla, Giorgio Delzanno, Ahmed Rezin...
Abstract. We present a novel approach for human gait recognition that inherently combines appearance and motion. Dynamic texture descriptors, Local Binary Patterns from Three Ortho...
Vili Kellokumpu, Guoying Zhao, Stan Z. Li, Matti P...
The paper presents a novel multi-view learning framework based on variational inference. We formulate the framework as a graph representation in form of graph factorization: the g...
We present a probabilistic generative model for learning semantic parsers from ambiguous supervision. Our approach learns from natural language sentences paired with world states ...
We propose a deblurring algorithm that explicitly takes into account the sparse characteristics of natural images and does not entail solving a numerically ill-conditioned backwar...