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» Learning the Structure of Dynamic Probabilistic Networks
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NIPS
1994
13 years 9 months ago
Boosting the Performance of RBF Networks with Dynamic Decay Adjustment
Radial Basis Function (RBF) Networks, also known as networks of locally{tuned processing units (see 6]) are well known for their ease of use. Most algorithms used to train these t...
Michael R. Berthold, Jay Diamond
ICCV
2003
IEEE
14 years 9 months ago
Tracking Articulated Body by Dynamic Markov Network
A new method for visual tracking of articulated objects is presented. Analyzing articulated motion is challenging because the dimensionality increase potentially demands tremendou...
Ying Wu, Gang Hua, Ting Yu
ISNN
2007
Springer
14 years 1 months ago
A Hierarchical Self-organizing Associative Memory for Machine Learning
This paper proposes novel hierarchical self-organizing associative memory architecture for machine learning. This memory architecture is characterized with sparse and local interco...
Janusz A. Starzyk, Haibo He, Yue Li
BIOINFORMATICS
2006
124views more  BIOINFORMATICS 2006»
13 years 7 months ago
Probabilistic inference of transcription factor concentrations and gene-specific regulatory activities
Motivation Quantitative estimation of the regulatory relationship between transcription factors and genes is a fundamental stepping stone when trying to develop models of cellular...
Guido Sanguinetti, Neil D. Lawrence, Magnus Rattra...
WEBI
2004
Springer
14 years 1 months ago
Adaptation and Personalization in Web-based Learning Support Systems
In order to achieve optimal efficiency in a learning process, individual learner needs his/her own personalized assistance. For a web-based open and dynamic learning environment, ...
Lisa Fan