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» Kernels and Regularization on Graphs
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84
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ICDM
2006
IEEE
146views Data Mining» more  ICDM 2006»
15 years 6 months ago
Boosting Kernel Models for Regression
This paper proposes a general boosting framework for combining multiple kernel models in the context of both classification and regression problems. Our main approach is built on...
Ping Sun, Xin Yao
111
Voted
ICDM
2005
IEEE
185views Data Mining» more  ICDM 2005»
15 years 6 months ago
Semi-Supervised Mixture of Kernels via LPBoost Methods
We propose an algorithm to construct classification models with a mixture of kernels from labeled and unlabeled data. The derived classifier is a mixture of models, each based o...
Jinbo Bi, Glenn Fung, Murat Dundar, R. Bharat Rao
101
Voted
DAGM
2006
Springer
15 years 4 months ago
Model Selection in Kernel Methods Based on a Spectral Analysis of Label Information
Abstract. We propose a novel method for addressing the model selection problem in the context of kernel methods. In contrast to existing methods which rely on hold-out testing or t...
Mikio L. Braun, Tilman Lange, Joachim M. Buhmann
118
Voted
TNN
2008
129views more  TNN 2008»
15 years 15 days ago
Data Visualization and Dimensionality Reduction Using Kernel Maps With a Reference Point
In this paper, a new kernel-based method for data visualization and dimensionality reduction is proposed. A reference point is considered corresponding to additional constraints ta...
Johan A. K. Suykens
100
Voted
NIPS
2008
15 years 2 months ago
An Extended Level Method for Efficient Multiple Kernel Learning
We consider the problem of multiple kernel learning (MKL), which can be formulated as a convex-concave problem. In the past, two efficient methods, i.e., Semi-Infinite Linear Prog...
Zenglin Xu, Rong Jin, Irwin King, Michael R. Lyu