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» The Computational Complexity of Probabilistic Planning
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CORR
2008
Springer
129views Education» more  CORR 2008»
13 years 9 months ago
Polynomial Linear Programming with Gaussian Belief Propagation
Abstract--Interior-point methods are state-of-the-art algorithms for solving linear programming (LP) problems with polynomial complexity. Specifically, the Karmarkar algorithm typi...
Danny Bickson, Yoav Tock, Ori Shental, Danny Dolev
COLING
2002
13 years 8 months ago
A Comparative Evaluation of Data-driven Models in Translation Selection of Machine Translation
We present a comparative evaluation of two data-driven models used in translation selection of English-Korean machine translation. Latent semantic analysis(LSA) and probabilistic ...
Yuseop Kim, Jeong Ho Chang, Byoung-Tak Zhang
PAMI
2007
187views more  PAMI 2007»
13 years 8 months ago
Supervised Learning of Semantic Classes for Image Annotation and Retrieval
—A probabilistic formulation for semantic image annotation and retrieval is proposed. Annotation and retrieval are posed as classification problems where each class is defined as...
Gustavo Carneiro, Antoni B. Chan, Pedro J. Moreno,...
FORMATS
2010
Springer
13 years 7 months ago
Expected Reachability-Time Games
In an expected reachability-time game (ERTG) two players, Min and Max, move a token along the transitions of a probabilistic timed automaton, so as to minimise and maximise, respec...
Vojtech Forejt, Marta Z. Kwiatkowska, Gethin Norma...
CVPR
2011
IEEE
13 years 4 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