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» Learning Generative Models with the Up-Propagation Algorithm
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IJON
2002
85views more  IJON 2002»
13 years 8 months ago
Learning statistically efficient features for speaker recognition
We apply independent component analysis (ICA) for extracting an optimal basis to the problem of finding efficient features for a speaker. The basis functions learned by the algori...
Gil-Jin Jang, Te-Won Lee, Yung-Hwan Oh
ICCV
2005
IEEE
14 years 11 months ago
Probabilistic Boosting-Tree: Learning Discriminative Models for Classification, Recognition, and Clustering
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
Zhuowen Tu
ECTEL
2008
Springer
13 years 10 months ago
Bridging the Gap between Practitioners and E-Learning Standards: A Domain-Specific Modeling Approach
Developing a learning design using IMS Learning Design (LD) is difficult for average practitioners because a high overhead of pedagogical knowledge and technical knowledge is requi...
Yongwu Miao, Tim Sodhi, Francis Brouns, Peter B. S...
NECO
2007
127views more  NECO 2007»
13 years 8 months ago
Visual Recognition and Inference Using Dynamic Overcomplete Sparse Learning
We present a hierarchical architecture and learning algorithm for visual recognition and other visual inference tasks such as imagination, reconstruction of occluded images, and e...
Joseph F. Murray, Kenneth Kreutz-Delgado
WEBDB
2010
Springer
155views Database» more  WEBDB 2010»
14 years 2 months ago
Learning Topical Transition Probabilities in Click Through Data with Regression Models
The transition of search engine usersā€™ intents has been studied for a long time. The knowledge of intent transition, once discovered, can yield a better understanding of how diļ...
Xiao Zhang, Prasenjit Mitra