We consider Bayesian detection/classification of discrete random parameters that are strongly dependent locally due to some deterministic local constraint. Based on the recently ...
Georg Kail, Jean-Yves Tourneret, Franz Hlawatsch, ...
We present a scalable quantum algorithm to solve binary consensus in a system of n crash-prone quantum processes. The algorithm works in O(polylog n) time sending O(n polylog n) qu...
Bogdan S. Chlebus, Dariusz R. Kowalski, Michal Str...
We describe a new scalable algorithm for semi-supervised training of conditional random fields (CRF) and its application to partof-speech (POS) tagging. The algorithm uses a simil...
A novel interactive segmentation framework comprising of a two stage s-t mincut is proposed. The framework has been designed keeping in mind the need to segment touching neuronal ...
The lack of large-scale, freely available and durable lexical resources, and the consequences for NLP, is widely acknowledged but the attempts to cope with usual bottlenecks preven...
Franck Sajous, Emmanuel Navarro, Bruno Gaume, Laur...