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» Learning a Generative Model for Structural Representations
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ISNN
2007
Springer
14 years 3 months ago
Sparse Coding in Sparse Winner Networks
This paper investigates a mechanism for reliable generation of sparse code in a sparsely connected, hierarchical, learning memory. Activity reduction is accomplished with local com...
Janusz A. Starzyk, Yinyin Liu, David D. Vogel
ICML
2009
IEEE
14 years 9 months ago
Unsupervised hierarchical modeling of locomotion styles
This paper describes an unsupervised learning technique for modeling human locomotion styles, such as distinct related activities (e.g. running and striding) or variations of the ...
Wei Pan, Lorenzo Torresani
UM
2007
Springer
14 years 3 months ago
Inducing User Affect Recognition Models for Task-Oriented Environments
Accurately recognizing users’ affective states could contribute to more productive and enjoyable interactions, particularly for task-oriented learning environments. In addition t...
Sunyoung Lee, Scott W. McQuiggan, James C. Lester
ML
2010
ACM
151views Machine Learning» more  ML 2010»
13 years 7 months ago
Inductive transfer for learning Bayesian networks
In several domains it is common to have data from different, but closely related problems. For instance, in manufacturing, many products follow the same industrial process but with...
Roger Luis, Luis Enrique Sucar, Eduardo F. Morales
KI
2007
Springer
14 years 3 months ago
Extending Markov Logic to Model Probability Distributions in Relational Domains
Abstract. Markov logic, as a highly expressive representation formalism that essentially combines the semantics of probabilistic graphical models with the full power of first-orde...
Dominik Jain, Bernhard Kirchlechner, Michael Beetz