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SDM
2007
SIAM
162views Data Mining» more  SDM 2007»
13 years 9 months ago
Probabilistic Joint Feature Selection for Multi-task Learning
We study the joint feature selection problem when learning multiple related classification or regression tasks. By imposing an automatic relevance determination prior on the hypo...
Tao Xiong, Jinbo Bi, R. Bharat Rao, Vladimir Cherk...
ALENEX
2001
105views Algorithms» more  ALENEX 2001»
13 years 9 months ago
A Probabilistic Spell for the Curse of Dimensionality
Range searches in metric spaces can be very di cult if the space is \high dimensional", i.e. when the histogram of distances has a large mean and a small variance. The so-cal...
Edgar Chávez, Gonzalo Navarro
ICML
2010
IEEE
13 years 7 months ago
Application of Machine Learning To Epileptic Seizure Detection
We present and evaluate a machine learning approach to constructing patient-specific classifiers that detect the onset of an epileptic seizure through analysis of the scalp EEG, a...
Ali H. Shoeb, John V. Guttag
CORR
2011
Springer
174views Education» more  CORR 2011»
12 years 11 months ago
Parameter Learning of Logic Programs for Symbolic-Statistical Modeling
We propose a logical/mathematical framework for statistical parameter learning of parameterized logic programs, i.e. de nite clause programs containing probabilistic facts with a ...
Yoshitaka Kameya, Taisuke Sato
BMCBI
2010
182views more  BMCBI 2010»
13 years 7 months ago
L2-norm multiple kernel learning and its application to biomedical data fusion
Background: This paper introduces the notion of optimizing different norms in the dual problem of support vector machines with multiple kernels. The selection of norms yields diff...
Shi Yu, Tillmann Falck, Anneleen Daemen, Lé...