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IJON
2006
104views more  IJON 2006»
14 years 10 months ago
Kernel methods and the exponential family
The success of Support Vector Machine (SVM) gave rise to the development of a new class of theoretically elegant learning machines which use a central concept of kernels and the a...
Stéphane Canu, Alexander J. Smola
106
Voted
JMLR
2006
124views more  JMLR 2006»
14 years 10 months ago
A Direct Method for Building Sparse Kernel Learning Algorithms
Many kernel learning algorithms, including support vector machines, result in a kernel machine, such as a kernel classifier, whose key component is a weight vector in a feature sp...
Mingrui Wu, Bernhard Schölkopf, Gökhan H...
ICML
2009
IEEE
15 years 11 months ago
A simpler unified analysis of budget perceptrons
The kernel Perceptron is an appealing online learning algorithm that has a drawback: whenever it makes an error it must increase its support set, which slows training and testing ...
Ilya Sutskever
111
Voted
SDM
2008
SIAM
161views Data Mining» more  SDM 2008»
14 years 11 months ago
Efficient Maximum Margin Clustering via Cutting Plane Algorithm
Maximum margin clustering (MMC) is a recently proposed clustering method, which extends the theory of support vector machine to the unsupervised scenario and aims at finding the m...
Bin Zhao, Fei Wang, Changshui Zhang
73
Voted
PRL
2006
106views more  PRL 2006»
14 years 10 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