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COLT
2008
Springer
13 years 9 months ago
How Local Should a Learning Method Be?
We consider the question of why modern machine learning methods like support vector machines outperform earlier nonparametric techniques like kNN. Our approach investigates the lo...
Alon Zakai, Yaacov Ritov
JMLR
2012
11 years 10 months ago
Sparse Additive Machine
We develop a high dimensional nonparametric classification method named sparse additive machine (SAM), which can be viewed as a functional version of support vector machine (SVM)...
Tuo Zhao, Han Liu
AAAI
2006
13 years 9 months ago
A Simple and Effective Method for Incorporating Advice into Kernel Methods
We propose a simple mechanism for incorporating advice (prior knowledge), in the form of simple rules, into support-vector methods for both classification and regression. Our appr...
Richard Maclin, Jude W. Shavlik, Trevor Walker, Li...
IJON
2006
104views more  IJON 2006»
13 years 7 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
JMLR
2006
124views more  JMLR 2006»
13 years 7 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...