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ICDM
2010
IEEE
127views Data Mining» more  ICDM 2010»
15 years 1 months ago
Learning Markov Network Structure with Decision Trees
Traditional Markov network structure learning algorithms perform a search for globally useful features. However, these algorithms are often slow and prone to finding local optima d...
Daniel Lowd, Jesse Davis
173
Voted
PE
2000
Springer
118views Optimization» more  PE 2000»
15 years 3 months ago
A probabilistic dynamic technique for the distributed generation of very large state spaces
Conventional methods for state space exploration are limited to the analysis of small systems because they suffer from excessive memory and computational requirements. We have dev...
William J. Knottenbelt, Peter G. Harrison, Mark Me...
122
Voted
EMMCVPR
2007
Springer
15 years 9 months ago
Bayesian Inference for Layer Representation with Mixed Markov Random Field
Abstract. This paper presents a Bayesian inference algorithm for image layer representation [26], 2.1D sketch [6], with mixed Markov random field. 2.1D sketch is an very important...
Ru-Xin Gao, Tianfu Wu, Song Chun Zhu, Nong Sang
JSAC
2006
109views more  JSAC 2006»
15 years 3 months ago
Polarized MIMO channels in 3-D: models, measurements and mutual information
4G systems are expected to support data rates of the order of 100 Mbps in the outdoor environment and 1 Gbps in the indoor/stationary environment. In order to support such large p...
Mansoor Shafi, Min Zhang, Aris L. Moustakas, Peter...
ICIP
1994
IEEE
16 years 5 months ago
Robust B-Spline Image Smoothing
In this work we present a new approach to two - dimensional robust spline smoothing. The proposed method is based on M-estimator algorithms but unlike in other M-estimator based i...
Marta Karczewicz, Moncef Gabbouj, Jaakko Astola