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IDA
2007
Springer
14 years 9 months ago
Removing biases in unsupervised learning of sequential patterns
Unsupervised sequence learning is important to many applications. A learner is presented with unlabeled sequential data, and must discover sequential patterns that characterize th...
Yoav Horman, Gal A. Kaminka
PR
2008
115views more  PR 2008»
14 years 9 months ago
Fractional order singular value decomposition representation for face recognition
Face Representation (FR) plays a typically important role in face recognition and methods such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) have be...
Jun Liu, Songcan Chen, Xiaoyang Tan
PR
2008
113views more  PR 2008»
14 years 9 months ago
Do unbalanced data have a negative effect on LDA?
For two-class discrimination, Ref. [1] claimed that, when covariance matrices of the two classes were unequal, a (class) unbalanced dataset had a negative effect on the performanc...
Jing-Hao Xue, D. Mike Titterington
PRESENCE
2008
110views more  PRESENCE 2008»
14 years 9 months ago
Modeling of Tool-Tissue Interactions for Computer-Based Surgical Simulation: A Literature Review
Surgical simulators present a safe and potentially effective method for surgical training, and can also be used in robot-assisted surgery for pre- and intra-operative planning. Ac...
Sarthak Misra, K. T. Ramesh, Allison M. Okamura
PR
2006
164views more  PR 2006»
14 years 9 months ago
Locally linear metric adaptation with application to semi-supervised clustering and image retrieval
Many computer vision and pattern recognition algorithms are very sensitive to the choice of an appropriate distance metric. Some recent research sought to address a variant of the...
Hong Chang, Dit-Yan Yeung