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AAAI
2012
7 years 2 months ago
Online Kernel Selection: Algorithms and Evaluations
Kernel methods have been successfully applied to many machine learning problems. Nevertheless, since the performance of kernel methods depends heavily on the type of kernels being...
Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Jinfeng Y...
AAAI
2012
7 years 2 months ago
Learning the Kernel Matrix with Low-Rank Multiplicative Shaping
Selecting the optimal kernel is an important and difficult challenge in applying kernel methods to pattern recognition. To address this challenge, multiple kernel learning (MKL) ...
Tomer Levinboim, Fei Sha
PAMI
2012
7 years 2 months ago
Domain Transfer Multiple Kernel Learning
—Cross-domain learning methods have shown promising results by leveraging labeled patterns from the auxiliary domain to learn a robust classifier for the target domain which has ...
Lixin Duan, Ivor W. Tsang, Dong Xu
JMLR
2012
7 years 2 months ago
Multi Kernel Learning with Online-Batch Optimization
In recent years there has been a lot of interest in designing principled classification algorithms over multiple cues, based on the intuitive notion that using more features shou...
Francesco Orabona, Jie Luo, Barbara Caputo
CVPR
2011
IEEE
8 years 7 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
CIARP
2010
Springer
8 years 9 months ago
A New Algorithm for Training SVMs Using Approximate Minimal Enclosing Balls
Abstract. It has been shown that many kernel methods can be equivalently formulated as minimal-enclosing-ball (MEB) problems in certain feature space. Exploiting this reduction eff...
Emanuele Frandi, Maria Grazia Gasparo, Stefano Lod...
ML
2007
ACM
144views Machine Learning» more  ML 2007»
8 years 11 months ago
Invariant kernel functions for pattern analysis and machine learning
In many learning problems prior knowledge about pattern variations can be formalized and beneficially incorporated into the analysis system. The corresponding notion of invarianc...
Bernard Haasdonk, Hans Burkhardt
IJON
2002
112views more  IJON 2002»
8 years 11 months ago
Kernel methods: a survey of current techniques
Kernel methods have become an increasingly popular tool for machine learning tasks such as classi
Colin Campbell
SIGKDD
2000
139views more  SIGKDD 2000»
8 years 11 months ago
Support Vector Machines: Hype or Hallelujah?
Support Vector Machines (SVMs) and related kernel methods have become increasingly popular tools for data mining tasks such as classification, regression, and novelty detection. T...
Kristin P. Bennett, Colin Campbell
PRL
2006
106views more  PRL 2006»
8 years 12 months ago
Invariances in kernel methods: From samples to objects
This paper presents a general method for incorporating prior knowledge into kernel methods such as Support Vector Machines. It applies when the prior knowledge can be formalized b...
Alexei Pozdnoukhov, Samy Bengio
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