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ORL
2011
13 years 2 months ago
Convex approximations to sparse PCA via Lagrangian duality
We derive a convex relaxation for cardinality constrained Principal Component Analysis (PCA) by using a simple representation of the L1 unit ball and standard Lagrangian duality. ...
Ronny Luss, Marc Teboulle
PR
2006
76views more  PR 2006»
13 years 7 months ago
Extending the relevant component analysis algorithm for metric learning using both positive and negative equivalence constraints
Relevant component analysis (RCA) is a recently proposed metric learning method for semi-supervised learning applications. It is a simple and efficient method that has been applie...
Dit-Yan Yeung, Hong Chang
IDEAL
2007
Springer
14 years 1 months ago
Analysis of Tiling Microarray Data by Learning Vector Quantization and Relevance Learning
We apply learning vector quantization to the analysis of tiling microarray data. As an example we consider the classification of C. elegans genomic probes as intronic or exonic. T...
Michael Biehl, Rainer Breitling, Yang Li
ICML
2003
IEEE
14 years 8 months ago
Learning Logic Programs for Layout Analysis Correction
Margherita Berardi, Michelangelo Ceci, Floriana Es...
ICALT
2008
IEEE
14 years 2 months ago
Interaction Analysis as a Multi-Support Approach of Social Computing for Learning, in the "Collaborative Era": Lessons Learned b
Apparently computer technology is shifting its focus, with individual users not being the main target any more. The evolution of Web 2.0 technologies is promoting the development ...
Tharrenos Bratitsis, Angelique Dimitracopoulou