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PR
2007
139views more  PR 2007»
15 years 3 months ago
Learning the kernel matrix by maximizing a KFD-based class separability criterion
The advantage of a kernel method often depends critically on a proper choice of the kernel function. A promising approach is to learn the kernel from data automatically. In this p...
Dit-Yan Yeung, Hong Chang, Guang Dai
SIGDIAL
2010
15 years 1 months ago
Advances in the Witchcraft Workbench Project
The Workbench for Intelligent exploraTion of Human ComputeR conversaTions is a new platform-independent open-source workbench designed for the analysis, mining and management of l...
Alexander Schmitt, Wolfgang Minker, Nada Sharaf
JMLR
2010
179views more  JMLR 2010»
14 years 10 months ago
PAC-Bayesian Analysis of Co-clustering and Beyond
We derive PAC-Bayesian generalization bounds for supervised and unsupervised learning models based on clustering, such as co-clustering, matrix tri-factorization, graphical models...
Yevgeny Seldin, Naftali Tishby
213
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PAMI
2012
13 years 6 months ago
A Least-Squares Framework for Component Analysis
— Over the last century, Component Analysis (CA) methods such as Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Canonical Correlation Analysis (CCA), Lap...
Fernando De la Torre
WSCG
2004
188views more  WSCG 2004»
15 years 5 months ago
Recognition of Motor Imagery Electroencephalography Using Independent Component Analysis and Machine Classifiers
Motor imagery electroencephalography (EEG), which embodies cortical potentials during mental simulation of left or right finger lifting tasks, can be used as neural input signals ...
Chih-I. Hung, Po-Lei Lee, Yu-Te Wu, Hui-Yun Chen, ...