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MLDM
1999
Springer
15 years 6 months ago
Non-hierarchical Clustering with Rival Penalized Competitive Learning for Information Retrieval
In large content-based image database applications, e cient information retrieval depends heavily on good indexing structures of the extracted features. While indexing techniques f...
Irwin King, Tak-Kan Lau
ICML
2010
IEEE
15 years 3 months ago
Bottom-Up Learning of Markov Network Structure
The structure of a Markov network is typically learned using top-down search. At each step, the search specializes a feature by conjoining it to the variable or feature that most ...
Jesse Davis, Pedro Domingos
ICML
2007
IEEE
16 years 3 months ago
The rendezvous algorithm: multiclass semi-supervised learning with Markov random walks
We consider the problem of multiclass classification where both labeled and unlabeled data points are given. We introduce and demonstrate a new approach for estimating a distribut...
Arik Azran
PR
2008
91views more  PR 2008»
15 years 2 months ago
Applying the multi-category learning to multiple video object extraction
Video object (VO) extraction is of great importance in multimedia processing. In recent years approaches have been proposed to deal with VO extraction as a classification problem....
Yi Liu, Yuan F. Zheng, Xiaotong Shen
ICMLA
2009
15 years 5 days ago
Learning Deep Neural Networks for High Dimensional Output Problems
State-of-the-art pattern recognition methods have difficulty dealing with problems where the dimension of the output space is large. In this article, we propose a new framework ba...
Benjamin Labbé, Romain Hérault, Cl&e...