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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...
BMVC
2010
13 years 5 months ago
Implicit Shape Kernel for Discriminative Learning of the Hough Transform Detector
The Hough transform provides an efficient way to detect objects. Various methods have been proposed to achieve discriminative learning of the Hough transform, but they have usuall...
Yimeng Zhang, Tsuhan Chen
QUESTA
2008
382views more  QUESTA 2008»
13 years 6 months ago
A note on stable flow-equivalent aggregation in closed networks
We introduce the Conditional Mean Value Analysis (CMVA) algorithm, an exact solution method for product-form load-dependent closed queueing networks that provides a numerically st...
Giuliano Casale
COLT
2008
Springer
13 years 8 months ago
On the Margin Explanation of Boosting Algorithms
Much attention has been paid to the theoretical explanation of the empirical success of AdaBoost. The most influential work is the margin theory, which is essentially an upper bou...
Liwei Wang, Masashi Sugiyama, Cheng Yang, Zhi-Hua ...
IDA
2002
Springer
13 years 6 months ago
Boosting strategy for classification
This paper introduces a strategy for training ensemble classifiers by analysing boosting within margin theory. We present a bound on the generalisation error of ensembled classifi...
Huma Lodhi, Grigoris J. Karakoulas, John Shawe-Tay...