— Given an arbitrary network of interconnected nodes, each with an initial value from a discrete set, we consider the problem of distributively disseminating these initial values...
We address the problem of segmenting 3D scan data into objects or object classes. Our segmentation framework is based on a subclass of Markov Random Fields (MRFs) which support ef...
Dragomir Anguelov, Benjamin Taskar, Vassil Chatalb...
In real sequence labeling tasks, statistics of many higher order features are not sufficient due to the training data sparseness, very few of them are useful. We describe Sparse H...
Abstract. Semantic inference is an important component in many natural language understanding applications. Classical approaches to semantic inference rely on logical representatio...
Ido Dagan, Roy Bar-Haim, Idan Szpektor, Iddo Green...
We investigate maximum likelihood parameter learning in Conditional Random Fields (CRF) and present an empirical study of pseudo-likelihood (PL) based approximations of the paramet...