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» Learning of Boolean Functions Using Support Vector Machines
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AIIA
2001
Springer
14 years 21 days ago
A New Machine Learning Approach to Fingerprint Classification
We present new fingerprint classification algorithms based on two machine learning approaches: support vector machines (SVMs), and recursive neural networks (RNNs). RNNs are traine...
Yuan Yao, Gian Luca Marcialis, Massimiliano Pontil...
NPL
2008
130views more  NPL 2008»
13 years 9 months ago
Adaptive Inverse Control of Excitation System with Actuator Uncertainty
: - This paper addresses an inverse controller design for excitation system with changing parameters and nonsmooth nonlinearities in the actuator. The existence of such nonlinearit...
Xiaofang Yuan, Yaonan Wang, Liang-Hong Wu
BMCBI
2010
98views more  BMCBI 2010»
13 years 9 months ago
Learning to predict expression efficacy of vectors in recombinant protein production
Background: Recombinant protein production is a useful biotechnology to produce a large quantity of highly soluble proteins. Currently, the most widely used production system is t...
Wen-Ching Chan, Po-Huang Liang, Yan-Ping Shih, Uen...
JUCS
2007
124views more  JUCS 2007»
13 years 9 months ago
An Improved SVM Based on Similarity Metric
: A novel support vector machine method for classification is presented in this paper. A modified kernel function based on the similarity metric and Riemannian metric is applied ...
Chaoyong Wang, Yanfeng Sun, Yanchun Liang
COLT
2004
Springer
14 years 2 months ago
Sparseness Versus Estimating Conditional Probabilities: Some Asymptotic Results
One of the nice properties of kernel classifiers such as SVMs is that they often produce sparse solutions. However, the decision functions of these classifiers cannot always be u...
Peter L. Bartlett, Ambuj Tewari