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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 10 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 6 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»
15 years 1 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 6 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 7 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...