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ICML
2004
IEEE
16 years 5 months ago
Learning associative Markov networks
Markov networks are extensively used to model complex sequential, spatial, and relational interactions in fields as diverse as image processing, natural language analysis, and bio...
Benjamin Taskar, Vassil Chatalbashev, Daphne Kolle...
COLT
1993
Springer
15 years 8 months ago
Parameterized Learning Complexity
We describe three applications in computational learning theory of techniques and ideas recently introduced in the study of parameterized computational complexity. (1) Using param...
Rodney G. Downey, Patricia A. Evans, Michael R. Fe...
IJCNN
2007
IEEE
15 years 10 months ago
A Wrapper for Projection Pursuit Learning
– Constructive algorithms are effective methods for designing Artificial Neural Networks (ANN) with good accuracy and generalization capability, yet with parsimonious network str...
Leonardo M. Holschuh, Clodoaldo Ap. M. Lima, Ferna...
ICIP
2007
IEEE
16 years 6 months ago
Monocular Tracking 3D People By Gaussian Process Spatio-Temporal Variable Model
Tracking 3D people from monocular video is often poorly constrained. To mitigate this problem, prior knowledge should be exploited. In this paper, the Gaussian process spatio-temp...
Junbiao Pang, Laiyun Qing, Qingming Huang, Shuqian...
IIE
2008
88views more  IIE 2008»
15 years 4 months ago
Development of Generative Learning Objects Using Feature Diagrams and Generative Techniques
Abstract. Learning Objects (LOs) play a key role for supporting eLearning. In general, however, the development of LOs remains a vague issue, because there is still no clearly defi...
Vytautas Stuikys, Robertas Damasevicius