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ALT
2001
Springer
15 years 6 months ago
Learning of Boolean Functions Using Support Vector Machines
This paper concerns the design of a Support Vector Machine (SVM) appropriate for the learning of Boolean functions. This is motivated by the need of a more sophisticated algorithm ...
Ken Sadohara
ALT
2000
Springer
15 years 6 months ago
On the Noise Model of Support Vector Machines Regression
Abstract. Support Vector Machines Regression (SVMR) is a learning technique where the goodness of fit is measured not by the usual quadratic loss function (the mean square error),...
Massimiliano Pontil, Sayan Mukherjee, Federico Gir...
ML
2002
ACM
220views Machine Learning» more  ML 2002»
14 years 9 months ago
Bayesian Methods for Support Vector Machines: Evidence and Predictive Class Probabilities
I describe a framework for interpreting Support Vector Machines (SVMs) as maximum a posteriori (MAP) solutions to inference problems with Gaussian Process priors. This probabilisti...
Peter Sollich
CORR
2011
Springer
163views Education» more  CORR 2011»
14 years 1 months ago
Suboptimal Solution Path Algorithm for Support Vector Machine
We consider a suboptimal solution path algorithm for the Support Vector Machine. The solution path algorithm is an effective tool for solving a sequence of a parametrized optimiz...
Masayuki Karasuyama, Ichiro Takeuchi
RECOMB
2002
Springer
15 years 10 months ago
Combining pairwise sequence similarity and support vector machines for remote protein homology detection
One key element in understanding the molecular machinery of the cell is to understand the meaning, or function, of each protein encoded in the genome. A very successful means of i...
Li Liao, William Stafford Noble