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TNN
2010
234views Management» more  TNN 2010»
13 years 2 months ago
Novel maximum-margin training algorithms for supervised neural networks
This paper proposes three novel training methods, two of them based on the back-propagation approach and a third one based on information theory for Multilayer Perceptron (MLP) bin...
Oswaldo Ludwig, Urbano Nunes
CSIE
2009
IEEE
14 years 2 months ago
A Computation Saving Partial-Sum-Global-Update Scheme for Perceptron Branch Predictor
With the pipeline deepen and issue width widen, the accuracy of branch predictor becomes more and more important to the performance of a microprocessor. State-of-theart researches...
Liqiang He
NIPS
2001
13 years 9 months ago
Kernel Machines and Boolean Functions
We give results about the learnability and required complexity of logical formulae to solve classification problems. These results are obtained by linking propositional logic with...
Adam Kowalczyk, Alex J. Smola, Robert C. Williamso...
ALT
2007
Springer
14 years 4 months ago
Learning Kernel Perceptrons on Noisy Data Using Random Projections
In this paper, we address the issue of learning nonlinearly separable concepts with a kernel classifier in the situation where the data at hand are altered by a uniform classific...
Guillaume Stempfel, Liva Ralaivola
IWANN
2005
Springer
14 years 1 months ago
Balanced Boosting with Parallel Perceptrons
Boosting constructs a weighted classifier out of possibly weak learners by successively concentrating on those patterns harder to classify. While giving excellent results in many ...
Iván Cantador, José R. Dorronsoro