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» Structure-Preserving Model Reduction
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WSC
2007
13 years 9 months ago
Feasibility study of variance reduction in the logistics composite model
The Logistics Composite Model (LCOM) is a stochastic, discrete-event simulation that relies on probabilities and random number generators to model scenarios in a maintenance unit ...
George P. Cole III, Alan W. Johnson, J. O. Miller
SIAMSC
2010
159views more  SIAMSC 2010»
13 years 5 months ago
Parameter and State Model Reduction for Large-Scale Statistical Inverse Problems
A greedy algorithm for the construction of a reduced model with reduction in both parameter and state is developed for efficient solution of statistical inverse problems governed b...
Chad Lieberman, Karen Willcox, Omar Ghattas
PARA
2004
Springer
14 years 23 days ago
A Model-Order Reduction Technique for Low Rank Rational Perturbations of Linear Eigenproblems
Large and sparse rational eigenproblems where the rational term is of low rank k arise in vibrations of fluid–solid structures and of plates with elastically attached loads. Exp...
Frank Blömeling, Heinrich Voss
SCL
2008
105views more  SCL 2008»
13 years 7 months ago
Computation of nonlinear balanced realization and model reduction based on Taylor series expansion
In this paper a computational algorithm for nonlinear balanced realization and model reduction based on Taylor series expansion is proposed. This algorithm requires recursive comp...
Kenji Fujimoto, Daisuke Tsubakino
TRS
2008
13 years 7 months ago
A Model of User-Oriented Reduct Construction for Machine Learning
An implicit assumption of many machine learning algorithms is that all attributes are of the same importance. An algorithm typically selects attributes based solely on their statis...
Yiyu Yao, Yan Zhao, Jue Wang, Suqing Han