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SIGIR
2006
ACM
14 years 4 months ago
Large scale semi-supervised linear SVMs
Large scale learning is often realistic only in a semi-supervised setting where a small set of labeled examples is available together with a large collection of unlabeled data. In...
Vikas Sindhwani, S. Sathiya Keerthi
BMCBI
2008
185views more  BMCBI 2008»
13 years 10 months ago
Mining clinical relationships from patient narratives
Background: The Clinical E-Science Framework (CLEF) project has built a system to extract clinically significant information from the textual component of medical records in order...
Angus Roberts, Robert J. Gaizauskas, Mark Hepple, ...
KDD
2005
ACM
163views Data Mining» more  KDD 2005»
14 years 10 months ago
Data Sparsity Issues in the Collaborative Filtering Framework
Abstract. With the amount of available information on the Web growing rapidly with each day, the need to automatically filter the information in order to ensure greater user effici...
Miha Grcar, Dunja Mladenic, Blaz Fortuna, Marko Gr...
GECCO
2007
Springer
235views Optimization» more  GECCO 2007»
14 years 4 months ago
Expensive optimization, uncertain environment: an EA-based solution
Real life optimization problems often require finding optimal solution to complex high dimensional, multimodal problems involving computationally very expensive fitness function e...
Maumita Bhattacharya
EVOW
2006
Springer
14 years 1 months ago
Robust SVM-Based Biomarker Selection with Noisy Mass Spectrometric Proteomic Data
Abstract. Computational analysis of mass spectrometric (MS) proteomic data from sera is of potential relevance for diagnosis, prognosis, choice of therapy, and study of disease act...
Elena Marchiori, Connie R. Jimenez, Mikkel West-Ni...