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Toward Tractable Global Solutions to Maximum-Likelihood Estimation Problems via Sparse Sum-of-Squares Relaxations.

, , and . CDC, page 3184-3189. IEEE, (2019)

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Linear prediction error methods for stochastic nonlinear models., and . Autom., (2019)Toward Tractable Global Solutions to Maximum-Likelihood Estimation Problems via Sparse Sum-of-Squares Relaxations., , and . CDC, page 3184-3189. IEEE, (2019)Consistent Estimators of Stochastic MIMO Wiener Models Based on Suboptimal Predictors., and . CDC, page 3842-3847. IEEE, (2018)Identification of stochastic nonlinear models using optimal estimating functions., and . Autom., (2020)DeepBayes - an estimator for parameter estimation in stochastic nonlinear dynamical models., , , and . CoRR, (2022)A simulated maximum likelihood method for estimation of stochastic Wiener systems., and . CDC, page 3060-3065. IEEE, (2016)An integrated approach for modeling and identification of perfusion bioreactors via basis flux modes., , , , and . Comput. Chem. Eng., (2021)Toward Tractable Global Solutions to Bayesian Point Estimation Problems via Sparse Sum-of-Squares Relaxations., , and . ACC, page 1501-1506. IEEE, (2020)Measures and LMIs for optimal control of piecewise-affine systems., , and . ECC, page 3173-3178. IEEE, (2013)Stochastic Approximation for Identification of Non-Linear Differential-Algebraic Equations with Process Disturbances., , , , and . CDC, page 6712-6717. IEEE, (2022)