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» Training Methods for Adaptive Boosting of Neural Networks
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62
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ICANN
2009
Springer
15 years 4 months ago
Evolving Memory Cell Structures for Sequence Learning
The best recent supervised sequence learning methods use gradient descent to train networks of miniature nets called memory cells. The most popular cell structure seems somewhat ar...
Justin Bayer, Daan Wierstra, Julian Togelius, J&uu...
69
Voted
ICANN
2005
Springer
15 years 3 months ago
Informational Energy Kernel for LVQ
We describe a kernel method which uses the maximization of Onicescu’s informational energy as a criteria for computing the relevances of input features. This adaptive relevance d...
Angel Cataron, Razvan Andonie
GVD
2009
128views Database» more  GVD 2009»
14 years 7 months ago
A Self-Adaptive Insert Strategy for Content-Based Multidimensional Database Storage
In this paper, we present the current development progress of our dynamic insert strategy based on the Intelligent Cluster Index (ICIx), which is a new type of multidimensional da...
Sebastian Leuoth, Wolfgang Benn
ICANN
2009
Springer
15 years 4 months ago
Adaptive Ensemble Models of Extreme Learning Machines for Time Series Prediction
Abstract. In this paper, we investigate the application of adaptive ensemble models of Extreme Learning Machines (ELMs) to the problem of one-step ahead prediction in (non)stationa...
Mark van Heeswijk, Yoan Miche, Tiina Lindh-Knuutil...
82
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TIT
2002
164views more  TIT 2002»
14 years 9 months ago
On the generalization of soft margin algorithms
Generalization bounds depending on the margin of a classifier are a relatively recent development. They provide an explanation of the performance of state-of-the-art learning syste...
John Shawe-Taylor, Nello Cristianini