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» A Reformulation of Support Vector Machines for General Confi...
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KDD
2004
ACM
166views Data Mining» more  KDD 2004»
14 years 6 months ago
Predicting prostate cancer recurrence via maximizing the concordance index
In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...
Lian Yan, David Verbel, Olivier Saidi
GECCO
2006
Springer
162views Optimization» more  GECCO 2006»
13 years 9 months ago
Evolutionary learning with kernels: a generic solution for large margin problems
In this paper we embed evolutionary computation into statistical learning theory. First, we outline the connection between large margin optimization and statistical learning and s...
Ingo Mierswa
MIR
2010
ACM
325views Multimedia» more  MIR 2010»
13 years 8 months ago
A classification-driven similarity matching framework for retrieval of biomedical images
This paper presents a classification-driven biomedical image retrieval system to bride the semantic gap by transforming image features to their global categories at different gran...
Md. Mahmudur Rahman, Sameer Antani, George R. Thom...
DAC
2005
ACM
13 years 8 months ago
A combined feasibility and performance macromodel for analog circuits
The need to reuse the performance macromodels of an analog circuit topology challenges existing regression based modeling techniques. A model of good reusability should have a num...
Mengmeng Ding, Ranga Vemuri
KDD
2008
ACM
178views Data Mining» more  KDD 2008»
14 years 6 months ago
Training structural svms with kernels using sampled cuts
Discriminative training for structured outputs has found increasing applications in areas such as natural language processing, bioinformatics, information retrieval, and computer ...
Chun-Nam John Yu, Thorsten Joachims