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14 years 11 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
16 years 29 days 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
82
Voted
BMCBI
2008
129views more  BMCBI 2008»
14 years 12 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»
14 years 11 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»
14 years 12 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...