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ECCV
2008
Springer
15 years 11 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
99
Voted
CVPR
2003
IEEE
15 years 11 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 9 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
85
Voted
AMAI
2004
Springer
15 years 2 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 7 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...