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GPEM
2006
117views more  GPEM 2006»
13 years 9 months ago
Introducing lateral thinking in search engines
Abstract. Too much information kills information. This common statement applies to huge databases, where state of the art search engines may retrieve hundreds of very similar docum...
Yann Landrin-Schweitzer, Pierre Collet, Evelyne Lu...
IPM
2008
139views more  IPM 2008»
13 years 9 months ago
Complex adaptive filtering user profile using graphical models
This article explores how to develop complex data driven user models that go beyond the bag of words model and topical relevance. We propose to learn from rich user specific info...
Yi Zhang 0001
AIIA
2005
Springer
14 years 2 months ago
Experimental Evaluation of Hierarchical Hidden Markov Models
Building profiles for processes and for interactive users is a important task in intrusion detection. This paper presents the results obtained with a Hierarchical Hidden Markov Mo...
Attilio Giordana, Ugo Galassi, Lorenza Saitta
JFR
2006
88views more  JFR 2006»
13 years 9 months ago
Discovering natural kinds of robot sensory experiences in unstructured environments
We derive categories directly from robot sensor data to address the symbol grounding problem. Unlike model-based approaches where human intuitive correspondences are sought betwee...
Daniel H. Grollman, Odest Chadwicke Jenkins, Frank...
ICCV
2009
IEEE
1318views Computer Vision» more  ICCV 2009»
15 years 1 months ago
Non-Local Sparse Models for Image Restoration
We propose in this paper to unify two different ap- proaches to image restoration: On the one hand, learning a basis set (dictionary) adapted to sparse signal descriptions has p...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...