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Optimization-based Tuning of Low-bandwidth Control in Spatially Distributed Systems
Optimization-based Tuning Low-bandwidth Control Spatially Distributed Systems
2015/7/10
We describe a new method for tuning a certain family of low-bandwidth controllers for linear time-invariant and spatially-invariant (LTSI) plants. We consider LTSI controllers with a fixed structure, ...
We present a framework and control policies for optimizing dynamic control of various self-tuning parameters over lifetime in the presence of circuit aging. Our framework introduces dynamic cooling as...
We formulate multi-input multi-output (MIMO) proportional-integral-derivative (PID) controller design as an optimization problem that involves nonconvex quadratic matrix inequalities. We propose a sim...
Parameter Tuning for a Multi-Fidelity Dynamical Model of the Magnetosphere
Computer Experiments Expected Improvement Geomagnetic Storm Inverse Problem Lorenz ‘96 Model Fidelity Sequential Design Uncertainty Quantification
2013/4/28
Geomagnetic storms play a critical role in space weather physics with the potential for far reaching economic impacts including power grid outages, air traffic re-routing, satellite damage and GPS dis...
TIGER: A Tuning-Insensitive Approach for Optimally Estimating Gaussian Graphical Models
TIGER Tuning-Insensitive Approach Optimally Estimating Gaussian Graphical Models
2012/11/22
We propose a new procedure for estimating high dimensional Gaussian graphical models. Our approach is asymptotically tuning-free and non-asymptotically tuning-insensitive: it requires very few efforts...
Performance Tuning Of J48 Algorithm For Prediction Of Soil Fertility
performance tuning prediction agriculture soil testing data mining classification.
2012/9/18
Data mining involves the systematic analysis of large data sets , and data mining in agricultural soil datasets is exciting and modern research area. The productive capacity of...
Consistent selection of tuning parameters via variable selection stability
kappa coefficient penalized regression selection consistency stability tuning
2012/9/17
Penalized regression models are popularly used in high-dimensional data analysis to conduct variable selection and model fitting simultaneously. Whereas success has been widely reported in literature,...
Tuning Tempered Transitions
Markov Chain Monte Carlo Multimodality Tempering Thermodynamic Integration
2010/10/15
The method of tempered transitions was proposed by Neal (1996) for tackling the difficulties arising when using Markov chain Monte Carlo to sample from multimodal distributions. In common with methods...