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EMMCVPR
1999
Springer
13 years 11 months ago
Markov Random Field Modelling of fMRI Data Using a Mean Field EM-algorithm
This paper considers the use of the EM-algorithm, combined with mean field theory, for parameter estimation in Markov random field models from unlabelled data. Special attention ...
Markus Svensén, Frithjof Kruggel, D. Yves v...
CVPR
2008
IEEE
14 years 9 months ago
Auto-context and its application to high-level vision tasks
The notion of using context information for solving highlevel vision problems has been increasingly realized in the field. However, how to learn an effective and efficient context...
Zhuowen Tu
JCISD
2006
114views more  JCISD 2006»
13 years 7 months ago
Ensemble of Linear Models for Predicting Drug Properties
We propose a new classification method for prediction of drug properties, called the Random Feature Subset Boosting for Linear Discriminant Analysis (LDA). The main novelty of this...
Tomasz Arodz, David A. Yuen, Arkadiusz Z. Dudek
TSP
2010
13 years 2 months ago
Randomized and distributed self-configuration of wireless networks: two-layer Markov random fields and near-optimality
Abstract--This work studies the near-optimality versus the complexity of distributed configuration management for wireless networks. We first develop a global probabilistic graphic...
Sung-eok Jeon, Chuanyi Ji
CVIU
2006
222views more  CVIU 2006»
13 years 7 months ago
Conditional models for contextual human motion recognition
We present algorithms for recognizing human motion in monocular video sequences, based on discriminative Conditional Random Field (CRF) and Maximum Entropy Markov Models (MEMM). E...
Cristian Sminchisescu, Atul Kanaujia, Dimitris N. ...