In this paper we address the problem of how to learn a structural prototype that can be used to represent the variations present in a set of trees. The prototype serves as a patte...
— Low-Density Parity-Check (LDPC) codes are typically characterized by a relatively high-complexity description, since a considerable amount of memory is required in order to sto...
An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, wit...
The goal of this paper is to find sparse and representative spatial priors that can be applied to part-based object localization. Assuming a GMRF prior over part configurations, w...
— Many applications offer a form-based environment for na¨ıve users for accessing databases without being familiar with the database schema or a structured query language. User...
Alkis Simitsis, Georgia Koutrika, Yannis E. Ioanni...