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» Learning of Boolean Functions Using Support Vector Machines
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ESWS
2008
Springer
13 years 10 months ago
Adding Data Mining Support to SPARQL Via Statistical Relational Learning Methods
Exploiting the complex structure of relational data enables to build better models by taking into account the additional information provided by the links between objects. We exten...
Christoph Kiefer, Abraham Bernstein, André ...
ACL
2008
13 years 10 months ago
Kernels on Linguistic Structures for Answer Extraction
Natural Language Processing (NLP) for Information Retrieval has always been an interesting and challenging research area. Despite the high expectations, most of the results indica...
Alessandro Moschitti, Silvia Quarteroni
ICIP
2008
IEEE
14 years 10 months ago
Emotional valence categorization using holistic image features
Can a machine learn to perceive emotions as evoked by an artwork? Here we propose an emotion categorization system, trained by ground truth from psychology studies. The training d...
Victoria Yanulevskaya, Jan van Gemert, Katharina R...
ICML
2003
IEEE
14 years 10 months ago
The Set Covering Machine with Data-Dependent Half-Spaces
We examine the set covering machine when it uses data-dependent half-spaces for its set of features and bound its generalization error in terms of the number of training errors an...
Mario Marchand, Mohak Shah, John Shawe-Taylor, Mar...
BIBE
2001
IEEE
14 years 22 days ago
Gene Classification using Expression Profiles: A Feasibility Study
As various genome sequencing projects have already been completed or are near completion, genome researchers are shifting their focus from structural genomics to functional genomi...
Michihiro Kuramochi, George Karypis