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» Learning Algorithms for Domain Adaptation
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GECCO
2009
Springer
14 years 3 days ago
The sensitivity of HyperNEAT to different geometric representations of a problem
HyperNEAT, a generative encoding for evolving artificial neural networks (ANNs), has the unique and powerful ability to exploit the geometry of a problem (e.g., symmetries) by enc...
Jeff Clune, Charles Ofria, Robert T. Pennock
CIKM
2004
Springer
13 years 11 months ago
Taxonomy-driven computation of product recommendations
Recommender systems have been subject to an enormous rise in popularity and research interest over the last ten years. At the same time, very large taxonomies for product classifi...
Cai-Nicolas Ziegler, Georg Lausen, Lars Schmidt-Th...
SDM
2010
SIAM
226views Data Mining» more  SDM 2010»
13 years 9 months ago
Two-View Transductive Support Vector Machines
Obtaining high-quality and up-to-date labeled data can be difficult in many real-world machine learning applications, especially for Internet classification tasks like review spam...
Guangxia Li, Steven C. H. Hoi, Kuiyu Chang
BMCBI
2007
154views more  BMCBI 2007»
13 years 7 months ago
Inferring biological networks with output kernel trees
Background: Elucidating biological networks between proteins appears nowadays as one of the most important challenges in systems biology. Computational approaches to this problem ...
Pierre Geurts, Nizar Touleimat, Marie Dutreix, Flo...
TCBB
2008
126views more  TCBB 2008»
13 years 7 months ago
Graphical Models of Residue Coupling in Protein Families
Abstract-- Many statistical measures and algorithmic techniques have been proposed for studying residue coupling in protein families. Generally speaking, two residue positions are ...
John Thomas, Naren Ramakrishnan, Chris Bailey-Kell...