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BMCBI
2010
150views more  BMCBI 2010»
14 years 7 months ago
Kernel based methods for accelerated failure time model with ultra-high dimensional data
Background: Most genomic data have ultra-high dimensions with more than 10,000 genes (probes). Regularization methods with L1 and Lp penalty have been extensively studied in survi...
Zhenqiu Liu, Dechang Chen, Ming Tan, Feng Jiang, R...
ICPR
2008
IEEE
15 years 11 months ago
Efficient background modeling through incremental Support Vector Data Description
Background modeling is an essential and important part of many high-level video processing applications. Recently, the Support Vector Data Description (SVDD) has been introduced f...
Alireza Tavakkoli, Mircea Nicolescu, George Bebis,...
ICASSP
2009
IEEE
15 years 4 months ago
Resampling auxiliary data for language model adaptation in machine translation for speech
Performance of n-gram language models depends to a large extent on the amount of training text material available for building the models and the degree to which this text matches...
Sameer Maskey, Abhinav Sethy
GFKL
2005
Springer
105views Data Mining» more  GFKL 2005»
15 years 3 months ago
Implications of Probabilistic Data Modeling for Mining Association Rules
Mining association rules is an important technique for discovering meaningful patterns in transaction databases. In the current literature, the properties of algorithms to mine ass...
Michael Hahsler, Kurt Hornik, Thomas Reutterer
PAMI
1998
128views more  PAMI 1998»
14 years 9 months ago
A Hierarchical Latent Variable Model for Data Visualization
—Visualization has proven to be a powerful and widely-applicable tool for the analysis and interpretation of multivariate data. Most visualization algorithms aim to find a projec...
Christopher M. Bishop, Michael E. Tipping