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114
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EMMCVPR
2007
Springer
15 years 8 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
JCB
2007
130views more  JCB 2007»
15 years 2 months ago
Bayesian Inference of MicroRNA Targets from Sequence and Expression Data
MicroRNAs (miRNAs) regulate a large proportion of mammalian genes by hybridizing to targeted messenger RNAs (mRNAs) and down-regulating their translation into protein. Although mu...
Jim C. Huang, Quaid Morris, Brendan J. Frey
112
Voted
ICPR
2004
IEEE
16 years 3 months ago
Multi-Class Extensions of the GLDB Feature Extraction Algorithm for Spectral Data
The Generalized Local Discriminant Bases (GLDB) algorithm proposed by Kumar, Ghosh and Crawford in [4], is a effective feature extraction method for spectral data. It identifies g...
Pavel Paclík, Robert P. W. Duin, Serguei Ve...
102
Voted
IWINAC
2007
Springer
15 years 8 months ago
EDNA: Estimation of Dependency Networks Algorithm
One of the key points in Estimation of Distribution Algorithms (EDAs) is the learning of the probabilistic graphical model used to guide the search: the richer the model the more ...
José A. Gámez, Juan L. Mateo, Jose M...
NLPRS
2001
Springer
15 years 7 months ago
A Bayesian Approach to Semi-Supervised Learning
Recent research in automated learning has focused on algorithms that learn from a combination of tagged and untagged data. Such algorithms can be referred to as semi-supervised in...
Rebecca F. Bruce