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ICIG
2009
IEEE
13 years 7 months ago
Statistical Modeling of Optical Flow
Optical flow estimation is one of the main subjects in computer vision. Many methods developed to compute the motion fields are built using standard heuristic formulation. In this...
Dongmin Ma, Véronique Prinet, Cyril Cassisa
BMCBI
2008
137views more  BMCBI 2008»
13 years 10 months ago
A dynamic Bayesian network approach to protein secondary structure prediction
Background: Protein secondary structure prediction method based on probabilistic models such as hidden Markov model (HMM) appeals to many because it provides meaningful informatio...
Xin-Qiu Yao, Huaiqiu Zhu, Zhen-Su She
PAKDD
2011
ACM
245views Data Mining» more  PAKDD 2011»
13 years 27 days ago
Finding Rare Classes: Adapting Generative and Discriminative Models in Active Learning
Discovering rare categories and classifying new instances of them is an important data mining issue in many fields, but fully supervised learning of a rare class classifier is pr...
Timothy M. Hospedales, Shaogang Gong, Tao Xiang
IWPT
2001
13 years 11 months ago
Probabilistic Modelling of Island-Driven Parsing
Two methods for stochastically modelling bidirectionality in chart parsing are presented. A probabilistic islanddriven parser which uses such models (either isolated or in combina...
Alicia Ageno, Horacio Rodríguez
ICML
2007
IEEE
14 years 11 months ago
Parameter learning for relational Bayesian networks
We present a method for parameter learning in relational Bayesian networks (RBNs). Our approach consists of compiling the RBN model into a computation graph for the likelihood fun...
Manfred Jaeger