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13 years 9 months ago
Covariance Regularization for Supervised Learning in High Dimensions
This paper studies the effect of covariance regularization for classific ation of high-dimensional data. This is done by fitting a mixture of Gaussians with a regularized covaria...
Daniel L. Elliott, Charles W. Anderson, Michael Ki...
ICPR
2006
IEEE
14 years 11 months ago
Dimensionality Reduction with Adaptive Kernels
1 A kernel determines the inductive bias of a learning algorithm on a specific data set, and it is beneficial to design specific kernel for a given data set. In this work, we propo...
Shuicheng Yan, Xiaoou Tang
BMCBI
2008
129views more  BMCBI 2008»
13 years 10 months ago
Mining phenotypes for gene function prediction
Background: Health and disease of organisms are reflected in their phenotypes. Often, a genetic component to a disease is discovered only after clearly defining its phenotype. In ...
Philip Groth, Bertram Weiss, Hans-Dieter Pohlenz, ...
BMCBI
2002
147views more  BMCBI 2002»
13 years 10 months ago
Expression profiling of human renal carcinomas with functional taxonomic analysis
Background: Molecular characterization has contributed to the understanding of the inception, progression, treatment and prognosis of cancer. Nucleic acid array-based technologies...
Michael A. Gieseg, Theresa Cody, Michael Z. Man, S...
BMCBI
2006
181views more  BMCBI 2006»
13 years 10 months ago
Array2BIO: from microarray expression data to functional annotation of co-regulated genes
Background: There are several isolated tools for partial analysis of microarray expression data. To provide an integrative, easy-to-use and automated toolkit for the analysis of A...
Gabriela G. Loots, Patrick S. G. Chain, Shalini Ma...