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» Structured Learning with Approximate Inference
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ECAI
2004
Springer
15 years 3 months ago
Learning Complex and Sparse Events in Long Sequences
The Hierarchical Hidden Markov Model (HHMM) is a well formalized tool suitable to model complex patterns in long temporal or spatial sequences. Even if effective algorithms are ava...
Marco Botta, Ugo Galassi, Attilio Giordana
CVPR
2011
IEEE
14 years 5 months ago
Learning Temporally Consistent Rigidities
We present a novel probabilistic framework for rigid tracking and segmentation of shapes observed from multiple cameras. Most existing methods have focused on solving each of thes...
Jean-Sebastien Franco, Edmond Boyer
AAAI
2008
15 years 4 days ago
Factored Models for Probabilistic Modal Logic
Modal logic represents knowledge that agents have about other agents' knowledge. Probabilistic modal logic further captures probabilistic beliefs about probabilistic beliefs....
Afsaneh Shirazi, Eyal Amir
ECCV
2002
Springer
15 years 11 months ago
Learning Shape from Defocus
We present a novel method for inferring three-dimensional shape from a collection of defocused images. It is based on the observation that defocused images are the null-space of ce...
Paolo Favaro, Stefano Soatto
SIGMOD
2007
ACM
125views Database» more  SIGMOD 2007»
15 years 10 months ago
Identifying meaningful return information for XML keyword search
Keyword search enables web users to easily access XML data without the need to learn a structured query language and to study possibly complex data schemas. Existing work has addr...
Ziyang Liu, Yi Chen