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ECCV
2008
Springer
16 years 1 months ago
Learning for Optical Flow Using Stochastic Optimization
Abstract. We present a technique for learning the parameters of a continuousstate Markov random field (MRF) model of optical flow, by minimizing the training loss for a set of grou...
Yunpeng Li, Daniel P. Huttenlocher
CVPR
2003
IEEE
16 years 1 months ago
Simultaneous Estimation of Left Ventricular Motion and Material Properties with Maximum a Posteriori Strategy
In addition to its technical merits as a challenging non-rigid motion and structural integrity analysis problem, quantitative estimation of cardiac regional functions and material...
Huafeng Liu, Pengcheng Shi
BMCBI
2008
186views more  BMCBI 2008»
14 years 11 months ago
Variable selection for large p small n regression models with incomplete data: Mapping QTL with epistases
Background: Identifying quantitative trait loci (QTL) for both additive and epistatic effects raises the statistical issue of selecting variables from a large number of candidates...
Min Zhang, Dabao Zhang, Martin T. Wells
AMAI
2004
Springer
15 years 5 months ago
Using the Central Limit Theorem for Belief Network Learning
Learning the parameters (conditional and marginal probabilities) from a data set is a common method of building a belief network. Consider the situation where we have known graph s...
Ian Davidson, Minoo Aminian
ICDM
2010
IEEE
101views Data Mining» more  ICDM 2010»
14 years 9 months ago
Tru-Alarm: Trustworthiness Analysis of Sensor Networks in Cyber-Physical Systems
A Cyber-Physical System (CPS) integrates physical devices (e.g., sensors, cameras) with cyber (or informational) components to form a situation-integrated analytical system that re...
Lu An Tang, Xiao Yu, Sangkyum Kim, Jiawei Han, Chi...