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JMLR
2006
116views more  JMLR 2006»
14 years 9 months ago
Step Size Adaptation in Reproducing Kernel Hilbert Space
This paper presents an online support vector machine (SVM) that uses the stochastic meta-descent (SMD) algorithm to adapt its step size automatically. We formulate the online lear...
S. V. N. Vishwanathan, Nicol N. Schraudolph, Alex ...
RECOMB
2005
Springer
15 years 10 months ago
Learning Interpretable SVMs for Biological Sequence Classification
Background: Support Vector Machines (SVMs) ? using a variety of string kernels ? have been successfully applied to biological sequence classification problems. While SVMs achieve ...
Christin Schäfer, Gunnar Rätsch, Sö...
AIME
2005
Springer
15 years 3 months ago
Learning Rules from Multisource Data for Cardiac Monitoring
This paper aims at formalizing the concept of learning rules from multisource data in a cardiac monitoring context. Our method has been implemented and evaluated on learning from d...
Élisa Fromont, Rene Quiniou, Marie-Odile Co...
ICML
2004
IEEE
15 years 3 months ago
Optimising area under the ROC curve using gradient descent
This paper introduces RankOpt, a linear binary classifier which optimises the area under the ROC curve (the AUC). Unlike standard binary classifiers, RankOpt adopts the AUC stat...
Alan Herschtal, Bhavani Raskutti
IDA
2010
Springer
14 years 8 months ago
Multi-dimensional data construction method with its application to learning from small-sample-sets
Insufficient training data is one of the major problems in neural network learning, because it leads to poor learning performance. In order to enhance an intelligent learning proc...
Hsiao-Fan Wang, Chun-Jung Huang