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» On the Convergence of Boosting Procedures
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SIAMSC
2008
129views more  SIAMSC 2008»
13 years 8 months ago
Iterative Solution of Piecewise Linear Systems
The correct formulation of numerical models for free-surface hydrodynamics often requires the solution of special linear systems whose coefficient matrix is a piecewise constant fu...
Luigi Brugnano, Vincenzo Casulli
ML
2007
ACM
106views Machine Learning» more  ML 2007»
13 years 8 months ago
Surrogate maximization/minimization algorithms and extensions
Abstract Surrogate maximization (or minimization) (SM) algorithms are a family of algorithms that can be regarded as a generalization of expectation-maximization (EM) algorithms. A...
Zhihua Zhang, James T. Kwok, Dit-Yan Yeung
PKDD
2001
Springer
104views Data Mining» more  PKDD 2001»
14 years 1 months ago
Data Reduction Using Multiple Models Integration
Large amount of available information does not necessarily imply that induction algorithms must use all this information. Samples often provide the same accuracy with less computat...
Aleksandar Lazarevic, Zoran Obradovic
NIPS
2007
13 years 10 months ago
Adaptive Embedded Subgraph Algorithms using Walk-Sum Analysis
We consider the estimation problem in Gaussian graphical models with arbitrary structure. We analyze the Embedded Trees algorithm, which solves a sequence of problems on tractable...
Venkat Chandrasekaran, Jason K. Johnson, Alan S. W...
IJCNN
2007
IEEE
14 years 2 months ago
Optimizing 0/1 Loss for Perceptrons by Random Coordinate Descent
—The 0/1 loss is an important cost function for perceptrons. Nevertheless it cannot be easily minimized by most existing perceptron learning algorithms. In this paper, we propose...
Ling Li, Hsuan-Tien Lin