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James C Spall
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Approximation algorithm
Bayesian probability
Stochastic optimization
Loss function
Complex systems
Adaptive control
Artificial neural network
System testing
Maximum likelihood
Covariance matrix
Convergence
Nonlinear system
Mathematical optimization
Monte Carlo method
System identification
Physics
Uncertainty
Finite difference
Estimation theory
Probability distribution
Stochastic approximation
Fisher information
Approximation theory
Stochastic process
Control system
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Approximation algorithm
Bayesian probability
Stochastic optimization
Loss function
Complex systems
Adaptive control
Artificial neural network
System testing
Maximum likelihood
Covariance matrix
Convergence
Nonlinear system
Mathematical optimization
Monte Carlo method
System identification
Physics
Uncertainty
Finite difference
Estimation theory
Probability distribution
Stochastic approximation
Fisher information
Approximation theory
Stochastic process
Control system
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James C Spall
Johns Hopkins University
185
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