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» Support vector machine for functional data classification
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ICML
2007
IEEE
16 years 7 months ago
On one method of non-diagonal regularization in sparse Bayesian learning
In the paper we propose a new type of regularization procedure for training sparse Bayesian methods for classification. Transforming Hessian matrix of log-likelihood function to d...
Dmitry Kropotov, Dmitry Vetrov
188
Voted
FSKD
2008
Springer
174views Fuzzy Logic» more  FSKD 2008»
15 years 7 months ago
A Hybrid Re-sampling Method for SVM Learning from Imbalanced Data Sets
Support Vector Machine (SVM) has been widely studied and shown success in many application fields. However, the performance of SVM drops significantly when it is applied to the pr...
Peng Li, Pei-Li Qiao, Yuan-Chao Liu
169
Voted
ICASSP
2011
IEEE
14 years 10 months ago
Estimation of fundamental frequency from surface electromyographic data: EMG-to-F0
In this paper, we present our recent studies of F0 estimation from the surface electromyographic (EMG) data using a Gaussian mixture model (GMM)-based voice conversion (VC) techni...
Keigo Nakamura, Matthias Janke, Michael Wand, Tanj...
COLT
2003
Springer
15 years 11 months ago
Learning from Uncertain Data
The application of statistical methods to natural language processing has been remarkably successful over the past two decades. But, to deal with recent problems arising in this ï¬...
Mehryar Mohri
ECML
2004
Springer
15 years 11 months ago
Using String Kernels to Identify Famous Performers from Their Playing Style
Abstract. In this paper we show a novel application of string kernels: that is to the problem of recognising famous pianists from their style of playing. The characterstics of perf...
Craig Saunders, David R. Hardoon, John Shawe-Taylo...