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ECML
2007
Springer
14 years 2 months ago
Principal Component Analysis for Large Scale Problems with Lots of Missing Values
Abstract. Principal component analysis (PCA) is a well-known classical data analysis technique. There are a number of algorithms for solving the problem, some scaling better than o...
Tapani Raiko, Alexander Ilin, Juha Karhunen
ACMICEC
2006
ACM
157views ECommerce» more  ACMICEC 2006»
14 years 2 months ago
Adaptive mechanism design: a metalearning approach
Auction mechanism design has traditionally been a largely analytic process, relying on assumptions such as fully rational bidders. In practice, however, bidders often exhibit unkn...
David Pardoe, Peter Stone, Maytal Saar-Tsechansky,...
CICLING
2008
Springer
13 years 10 months ago
Semantic and Syntactic Features for Dutch Coreference Resolution
We investigate the effect of encoding additional semantic and syntactic information sources in a classification-based machine learning approach to the task of coreference resolutio...
Iris Hendrickx, Véronique Hoste, Walter Dae...
JCB
2006
185views more  JCB 2006»
13 years 8 months ago
A Probabilistic Methodology for Integrating Knowledge and Experiments on Biological Networks
Biological systems are traditionally studied by focusing on a specific subsystem, building an intuitive model for it, and refining the model using results from carefully designed ...
Irit Gat-Viks, Amos Tanay, Daniela Raijman, Ron Sh...
BMCBI
2008
97views more  BMCBI 2008»
13 years 8 months ago
SiteSeek: Post-translational modification analysis using adaptive locality-effective kernel methods and new profiles
Background: Post-translational modifications have a substantial influence on the structure and functions of protein. Post-translational phosphorylation is one of the most common m...
Paul D. Yoo, Yung Shwen Ho, Bing Bing Zhou, Albert...