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» On the convergence of Hill's method
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GECCO
2000
Springer
138views Optimization» more  GECCO 2000»
15 years 4 months ago
Domain Knowledge and Representation in Genetic Algorithms for Real World Scheduling Problems
This paper discusses the issues that arise in the design and implementation of an industrialstrength evolutionary-based system for the optimization of the monthly work schedules f...
Ioannis T. Christou, Armand Zakarian
AUTOMATICA
2006
90views more  AUTOMATICA 2006»
15 years 1 months ago
An ISS-modular approach for adaptive neural control of pure-feedback systems
Controlling non-affine non-linear systems is a challenging problem in control theory. In this paper, we consider adaptive neural control of a completely non-affine pure-feedback s...
Cong Wang, David J. Hill, S. S. Ge, Guanrong Chen
SIAMSC
2011
219views more  SIAMSC 2011»
14 years 8 months ago
Fast Algorithms for Bayesian Uncertainty Quantification in Large-Scale Linear Inverse Problems Based on Low-Rank Partial Hessian
We consider the problem of estimating the uncertainty in large-scale linear statistical inverse problems with high-dimensional parameter spaces within the framework of Bayesian inf...
H. P. Flath, Lucas C. Wilcox, Volkan Akcelik, Judi...
CEJCS
2011
80views more  CEJCS 2011»
14 years 1 months ago
Evaluating distributed real-time and embedded system test correctness using system execution traces
: Effective validation of distributed real-time and embedded (DRE) system quality-of-service (QoS) properties (e.g., event prioritization, latency, and throughput) requires testin...
James H. Hill, Pooja Varshneya, Douglas C. Schmidt
AIPS
2006
15 years 2 months ago
Learning to Do HTN Planning
We describe HDL, an algorithm that learns HTN domain descriptions by examining plan traces produced by an expert problem-solver. Prior work on learning HTN methods requires that a...
Okhtay Ilghami, Dana S. Nau, Héctor Mu&ntil...