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VECPAR
2004
Springer
14 years 1 months ago
Domain Decomposition Methods for PDE Constrained Optimization Problems
Abstract. Optimization problems constrained by nonlinear partial differential equations have been the focus of intense research in scientific computing lately. Current methods for...
Ernesto E. Prudencio, Richard H. Byrd, Xiao-Chuan ...
CCE
2008
13 years 7 months ago
Global optimization of multiscenario mixed integer nonlinear programming models arising in the synthesis of integrated water net
The problem of optimal synthesis of an integrated water system is addressed in this work, where water using processes and water treatment operations are combined into a single net...
Ramkumar Karuppiah, Ignacio E. Grossmann
JAIR
2002
163views more  JAIR 2002»
13 years 7 months ago
Efficient Reinforcement Learning Using Recursive Least-Squares Methods
The recursive least-squares (RLS) algorithm is one of the most well-known algorithms used in adaptive filtering, system identification and adaptive control. Its popularity is main...
Xin Xu, Hangen He, Dewen Hu
SIAMSC
2008
147views more  SIAMSC 2008»
13 years 7 months ago
Global and Finite Termination of a Two-Phase Augmented Lagrangian Filter Method for General Quadratic Programs
We present a two-phase algorithm for solving large-scale quadratic programs (QPs). In the first phase, gradient-projection iterations approximately minimize an augmented Lagrangian...
Michael P. Friedlander, Sven Leyffer
JMLR
2006
389views more  JMLR 2006»
13 years 7 months ago
A Very Fast Learning Method for Neural Networks Based on Sensitivity Analysis
This paper introduces a learning method for two-layer feedforward neural networks based on sensitivity analysis, which uses a linear training algorithm for each of the two layers....
Enrique Castillo, Bertha Guijarro-Berdiñas,...