A Metamorphosis of Canonical Correlation Analysis into Multivariate Maximum Margin Learning

Sandor Szedmak, Tijl De Bie, David Hardoon
A metamorphosis of Canonical Correlation Analysis into Multivariate Maximum Margin Learning
Proceedings of the 15th European Symposium on Artificial Neural Networks (ESANN 2007), Bruges, April 2007.

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By tijldebie at 07/24/2009 - 10:44

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Statistical foundations of data mining
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An end-to-end machine learning system for harmonic analysis of music
An Information Theoretic Framework for Data Mining
Maximum Entropy Models and Subjective Interestingness: an Application to Tiles in Binary Databases
Leveraging Noisy Online Databases for Use in Chord Recognition
Using Online Chord Databases to Enhance Chord Recognition
Refining Causality: Who Copied from Whom?
Mining the Correlation between Lyrical and Audio Features
Interesting Multi-Relational Patterns
Maximum Entropy Modelling for Assessing Results on Real-Valued Data
DISTILLER: a data integration framework to reveal condition dependency of complex regulons in Escherichia coli
MINI: Mining Informative Non-redundant Itemsets

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A Metamorphosis of Canonical Correlation Analysis into Multivariate Maximum Margin Learning

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Selected Publications