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» A PAC Bound for Approximate Support Vector Machines
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TNN
2008
182views more  TNN 2008»
13 years 7 months ago
Large-Scale Maximum Margin Discriminant Analysis Using Core Vector Machines
Abstract--Large-margin methods, such as support vector machines (SVMs), have been very successful in classification problems. Recently, maximum margin discriminant analysis (MMDA) ...
Ivor Wai-Hung Tsang, András Kocsor, James T...
STOC
2009
ACM
87views Algorithms» more  STOC 2009»
14 years 8 months ago
Randomly supported independence and resistance
We prove that for any positive integer k, there is a constant ck such that a randomly selected set of cknk log n Boolean vectors with high probability supports a balanced k-wise i...
Per Austrin, Johan Håstad
ECCC
2000
140views more  ECCC 2000»
13 years 7 months ago
Randomized Approximation Schemes for Scheduling Unrelated Parallel Machines
We consider the problem of Scheduling n Independent Jobs on m Unrelated Parallel Machines, when the number of machines m is xed. We address the standard problem of minimizing the ...
Pavlos Efraimidis, Paul G. Spirakis
ICANN
2007
Springer
13 years 11 months ago
Resilient Approximation of Kernel Classifiers
Abstract. Trained support vector machines (SVMs) have a slow runtime classification speed if the classification problem is noisy and the sample data set is large. Approximating the...
Thorsten Suttorp, Christian Igel
ML
2002
ACM
140views Machine Learning» more  ML 2002»
13 years 7 months ago
A Probabilistic Framework for SVM Regression and Error Bar Estimation
In this paper, we elaborate on the well-known relationship between Gaussian Processes (GP) and Support Vector Machines (SVM) under some convex assumptions for the loss functions. ...
Junbin Gao, Steve R. Gunn, Chris J. Harris, Martin...