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» A New Discriminative Kernel From Probabilistic Models
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CVPR
2006
IEEE
15 years 11 months ago
Modeling and Classifying Breast Tissue Density in Mammograms
We present a new approach to model and classify breast parenchymal tissue. Given a mammogram, first, we will discover the distribution of the different tissue densities in an unsu...
Anna Bosch, Arnau Oliver, Joan Martí, Xavie...
AAAI
2012
13 years 4 days ago
Learning the Kernel Matrix with Low-Rank Multiplicative Shaping
Selecting the optimal kernel is an important and difficult challenge in applying kernel methods to pattern recognition. To address this challenge, multiple kernel learning (MKL) ...
Tomer Levinboim, Fei Sha
ACIIDS
2010
IEEE
204views Database» more  ACIIDS 2010»
15 years 2 months ago
An Unsupervised Learning and Statistical Approach for Vietnamese Word Recognition and Segmentation
There are two main topics in this paper: (i) Vietnamese words are recognized and sentences are segmented into words by using probabilistic models; (ii) the optimum probabilistic mo...
Hieu Le Trung, Vu Le Anh, Kien Le Trung
BMCBI
2007
144views more  BMCBI 2007»
14 years 9 months ago
Motif kernel generated by genetic programming improves remote homology and fold detection
Background: Protein remote homology detection is a central problem in computational biology. Most recent methods train support vector machines to discriminate between related and ...
Tony Håndstad, Arne J. H. Hestnes, Pål...
ICASSP
2011
IEEE
14 years 1 months ago
Increasing discriminative capability on MAP-based mapping function estimation for acoustic model adaptation
In this study, we propose increasing discriminative power on the maximum a posteriori (MAP)-based mapping function estimation for acoustic model adaptation. Based on the effective...
Yu Tsao, Ryosuke Isotani, Hisashi Kawai, Satoshi N...