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» Prediction on Spike Data Using Kernel Algorithms
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ICML
2006
IEEE
14 years 8 months ago
Kernelizing the output of tree-based methods
We extend tree-based methods to the prediction of structured outputs using a kernelization of the algorithm that allows one to grow trees as soon as a kernel can be defined on the...
Florence d'Alché-Buc, Louis Wehenkel, Pierr...
ICML
2006
IEEE
14 years 8 months ago
Fast and space efficient string kernels using suffix arrays
String kernels which compare the set of all common substrings between two given strings have recently been proposed by Vishwanathan & Smola (2004). Surprisingly, these kernels...
Choon Hui Teo, S. V. N. Vishwanathan
TOG
2008
102views more  TOG 2008»
13 years 7 months ago
Real-time data driven deformation using kernel canonical correlation analysis
Achieving intuitive control of animated surface deformation while observing a specific style is an important but challenging task in computer graphics. Solutions to this task can ...
Wei-Wen Feng, Byung-Uck Kim, Yizhou Yu
PAKDD
2009
ACM
233views Data Mining» more  PAKDD 2009»
14 years 7 days ago
A Kernel Framework for Protein Residue Annotation
Abstract. Over the last decade several prediction methods have been developed for determining structural and functional properties of individual protein residues using sequence and...
Huzefa Rangwala, Christopher Kauffman, George Kary...
CSDA
2007
128views more  CSDA 2007»
13 years 7 months ago
Regularized linear and kernel redundancy analysis
Redundancy analysis (RA) is a versatile technique used to predict multivariate criterion variables from multivariate predictor variables. The reduced-rank feature of RA captures r...
Yoshio Takane, Heungsun Hwang