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» Incremental and Decremental Support Vector Machine Learning
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CVPR
2005
IEEE
15 years 12 months ago
A Semi-Supervised Active Learning Framework for Image Retrieval
Although recent studies have shown that unlabeled data are beneficial to boosting the image retrieval performance, very few approaches for image retrieval can learn with labeled a...
Steven C. H. Hoi, Michael R. Lyu
IJCNN
2006
IEEE
15 years 3 months ago
Non-Relevance Feedback Document Retrieval based on One Class SVM and SVDD
— This paper reports a new document retrieval method using non-relevant documents. Especially, this paper reports a comparison of retrieval efficiency between One Class Support ...
Takashi Onoda, Hiroshi Murata, Seiji Yamada
IDEAL
2005
Springer
15 years 3 months ago
Exploiting Sequence Dependencies in the Prediction of Peroxisomal Proteins
Prediction of peroxisomal matrix proteins generally depends on the presence of one of two distinct motifs at the end of the amino acid sequence. PTS1 peroxisomal proteins have a we...
Mark Wakabayashi, John Hawkins, Stefan Maetschke, ...
ICML
2008
IEEE
15 years 10 months ago
Training SVM with indefinite kernels
Similarity matrices generated from many applications may not be positive semidefinite, and hence can't fit into the kernel machine framework. In this paper, we study the prob...
Jianhui Chen, Jieping Ye
SEAL
1998
Springer
15 years 2 months ago
Genetic Programming with Active Data Selection
Genetic programming evolves Lisp-like programs rather than fixed size linear strings. This representational power combined with generality makes genetic programming an interesting ...
Byoung-Tak Zhang, Dong-Yeon Cho