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» Learning with Idealized Kernels
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ICML
2006
IEEE
14 years 10 months ago
Kernel Predictive Linear Gaussian models for nonlinear stochastic dynamical systems
The recent Predictive Linear Gaussian model (or PLG) improves upon traditional linear dynamical system models by using a predictive representation of state, which makes consistent...
David Wingate, Satinder P. Singh
CVPR
2006
IEEE
15 years 23 hour ago
Graph Laplacian Kernels for Object Classification from a Single Example
Classification with only one labeled example per class is a challenging problem in machine learning and pattern recognition. While there have been some attempts to address this pr...
Hong Chang, Dit-Yan Yeung
SDM
2009
SIAM
152views Data Mining» more  SDM 2009»
14 years 7 months ago
Multiple Kernel Clustering.
Maximum margin clustering (MMC) has recently attracted considerable interests in both the data mining and machine learning communities. It first projects data samples to a kernel...
Bin Zhao, James T. Kwok, Changshui Zhang
COLT
2004
Springer
14 years 3 months ago
Statistical Properties of Kernel Principal Component Analysis
The main goal of this paper is to prove inequalities on the reconstruction error for Kernel Principal Component Analysis. With respect to previous work on this topic, our contribu...
Laurent Zwald, Olivier Bousquet, Gilles Blanchard
CVPR
2011
IEEE
13 years 5 months ago
Local Isomorphism to Solve the Pre-image Problem in Kernel Methods
Kernel methods have been popular over the last decade to solve many computer vision, statistics and machine learning problems. An important, both theoretically and practically, op...
Dong Huang, Yuandong Tian, Fernando DelaTorre