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ICML
2007
IEEE
16 years 7 months ago
Bottom-up learning of Markov logic network structure
Markov logic networks (MLNs) are a statistical relational model that consists of weighted firstorder clauses and generalizes first-order logic and Markov networks. The current sta...
Lilyana Mihalkova, Raymond J. Mooney
ECCV
2002
Springer
16 years 8 months ago
A Markov Chain Monte Carlo Approach to Stereovision
We propose Markov chain Monte Carlo sampling methods to address uncertainty estimation in disparity computation. We consider this problem at a postprocessing stage, i.e. once the d...
Julien Sénégas
CAV
2007
Springer
113views Hardware» more  CAV 2007»
16 years 24 days ago
Three-Valued Abstraction for Continuous-Time Markov Chains
lued Abstraction for Continuous-Time Markov Chains⋆ Joost-Pieter Katoen1 , Daniel Klink1 , Martin Leucker2 , and Verena Wolf3 RWTH Aachen University1 , TU Munich2 , University of...
Joost-Pieter Katoen, Daniel Klink, Martin Leucker,...
CORR
2010
Springer
147views Education» more  CORR 2010»
15 years 6 months ago
High-Rate Quantization for the Neyman-Pearson Detection of Hidden Markov Processes
This paper investigates the decentralized detection of Hidden Markov Processes using the NeymanPearson test. We consider a network formed by a large number of distributed sensors....
Joffrey Villard, Pascal Bianchi, Eric Moulines, Pa...
CVPR
2008
IEEE
16 years 8 months ago
One step beyond histograms: Image representation using Markov stationary features
This paper proposes a general framework called Markov stationary features (MSF) to extend histogram based features. The MSF characterizes the spatial co-occurrence of histogram pa...
Jianguo Li, Weixin Wu, Tao Wang, Yimin Zhang