Developing scalable algorithms for solving partially observable Markov decision processes (POMDPs) is an important challenge. One promising approach is based on representing POMDP...
Christopher Amato, Daniel S. Bernstein, Shlomo Zil...
Shared nothing multiprocessor archit.ecture is known t.obe more scalable to support very large databases. Compared to other join strategies, a hash-ba9ed join algorithm is particu...
Named Entity recognition (NER) is an important part of many natural language processing tasks. Current approaches often employ machine learning techniques and require supervised d...
This paper investigates a new learning formulation called dynamic group sparsity. It is a natural extension of the standard sparsity concept in compressive sensing, and is motivat...
This paper proposes some Markov Random Field (MRF) models for restoration of stereo disparity maps. The main aspect is the use of confidence maps provided by the Symmetric Multipl...
Andrea Fusiello, Umberto Castellani, Vittorio Muri...