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» Learning nonlinear dynamic models
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ENGL
2008
153views more  ENGL 2008»
15 years 27 days ago
Neural Network NARMA Control of a Gyroscopic Inverted Pendulum
The objective herein is to demonstrate the feasibility of a real-time digital control of an inverted pendulum for modeling and control, with emphasis on nonlinear auto regressive m...
F. Chetouane, S. Darenfed
104
Voted
FLAIRS
2007
15 years 3 months ago
Managing Dynamic Contexts Using Failure-Driven Stochastic Models
We describe an architecture for representing and managing context shifts that supports dynamic data interpretation. This architecture utilizes two layers of learning and three lay...
Nikita A. Sakhanenko, George F. Luger, Carl R. Ste...
JMLR
2002
106views more  JMLR 2002»
15 years 15 days ago
Some Greedy Learning Algorithms for Sparse Regression and Classification with Mercer Kernels
We present some greedy learning algorithms for building sparse nonlinear regression and classification models from observational data using Mercer kernels. Our objective is to dev...
Prasanth B. Nair, Arindam Choudhury 0002, Andy J. ...
86
Voted
ICML
2006
IEEE
16 years 1 months ago
Predictive linear-Gaussian models of controlled stochastic dynamical systems
We introduce the controlled predictive linearGaussian model (cPLG), a model that uses predictive state to model discrete-time dynamical systems with real-valued observations and v...
Matthew R. Rudary, Satinder P. Singh
97
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CCE
2004
15 years 21 days ago
Continuous reformulations of discrete-continuous optimization problems
This paper treats the solution of nonlinear optimization problems involving discrete decision variables, also known as generalized disjunctive programming (GDP) or mixed-integer n...
Oliver Stein, Jan Oldenburg, Wolfgang Marquardt