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CVPR
2009
IEEE
15 years 2 months ago
Let the Kernel Figure it Out; Principled Learning of Pre-processing for Kernel Classifiers
Most modern computer vision systems for high-level tasks, such as image classification, object recognition and segmentation, are based on learning algorithms that are able to se...
Peter V. Gehler, Sebastian Nowozin
CVPR
2005
IEEE
14 years 9 months ago
Diagram Structure Recognition by Bayesian Conditional Random Fields
Hand-drawn diagrams present a complex recognition problem. Elements of the diagram are often individually ambiguous, and require context to be interpreted. We present a recognitio...
Yuan (Alan) Qi, Martin Szummer, Thomas P. Minka
BMCBI
2010
115views more  BMCBI 2010»
13 years 7 months ago
Assessment and optimisation of normalisation methods for dual-colour antibody microarrays
Background: Recent advances in antibody microarray technology have made it possible to measure the expression of hundreds of proteins simultaneously in a competitive dual-colour a...
Martin Sill, Christoph Schroder, Jörg D. Hohe...
JMLR
2006
156views more  JMLR 2006»
13 years 7 months ago
Large Scale Multiple Kernel Learning
While classical kernel-based learning algorithms are based on a single kernel, in practice it is often desirable to use multiple kernels. Lanckriet et al. (2004) considered conic ...
Sören Sonnenburg, Gunnar Rätsch, Christi...
RECOMB
2010
Springer
13 years 9 months ago
Subnetwork State Functions Define Dysregulated Subnetworks in Cancer
Abstract. Emerging research demonstrates the potential of proteinprotein interaction (PPI) networks in uncovering the mechanistic bases of cancers, through identification of intera...
Salim A. Chowdhury, Rod K. Nibbe, Mark R. Chance, ...