Convex optimization problems arising in applications, possibly as approximations of intractable problems, are often structured and large scale. When the data are noisy, it is of i...
Documents often have inherently parallel structure: they may consist of a text and ries, or an abstract and a body, or parts presenting alternative views on the same problem. Reve...
A hierarchical framework for the recognition of complex deformable shapes is developed. In extension to traditional approaches an additional layer of control is introduced to guid...
Confidence-Weighted linear classifiers (CW) and its successors were shown to perform well on binary and multiclass NLP problems. In this paper we extend the CW approach for sequen...
In this paper a general framework for separation logic inside the HOL theorem prover is presented. This framework is based on Abeparation Logic. It contains a model of an abstract,...