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NN
2006
Springer
114views Neural Networks» more  NN 2006»
13 years 8 months ago
Modular learning models in forecasting natural phenomena
Modular model is a particular type of committee machine and is comprised of a set of specialized (local) models each of which is responsible for a particular region of the input s...
Dimitri P. Solomatine, Michael Baskara L. A. Siek
PR
2006
147views more  PR 2006»
13 years 8 months ago
Robust locally linear embedding
In the past few years, some nonlinear dimensionality reduction (NLDR) or nonlinear manifold learning methods have aroused a great deal of interest in the machine learning communit...
Hong Chang, Dit-Yan Yeung
PR
2006
152views more  PR 2006»
13 years 8 months ago
Edit distance-based kernel functions for structural pattern classification
A common approach in structural pattern classification is to define a dissimilarity measure on patterns and apply a distance-based nearest-neighbor classifier. In this paper, we i...
Michel Neuhaus, Horst Bunke
SIMPRA
2008
94views more  SIMPRA 2008»
13 years 8 months ago
A simulation based experimental design to analyze factors affecting production flow time
In this paper we analyze and evaluate the effects of some pre-defined process parameters on the performance of a manufacturing system. These parameters include two different plant...
Banu Y. Ekren, Arslan M. Ornek
INFORMS
2007
123views more  INFORMS 2007»
13 years 8 months ago
Constructing Ensembles from Data Envelopment Analysis
It has been shown in prior work in management science, statistics and machine learning that using an ensemble of models often results in better performance than using a single ‘...
Zhiqiang Zheng, Balaji Padmanabhan