An efficient averaged stochastic Gauss-Newton algorithm for estimating parameters of nonlinear regressions models

Cites Work

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Fast estimation of the median covariation matrix with application to online robust principal components analysis
A stochastic quasi-Newton method for large-scale optimization
Estimating a regression function
Asymptotic theory of nonlinear least squares estimation
On asymptotically efficient recursive estimation
Consistency for the least squares estimator in nonparametric regression
Statistical tools for nonlinear regression. A practical guide with S-PLUS and R examples.
On least squares estimation for stable nonlinear AR processes
On the almost sure asymptotic behaviour of stochastic algorithm
Strong consistency in nonlinear stochastic regression models.
Asymptotic properties of nonlinear least squares estimates in stochastic regression models
Online estimation of the geometric median in Hilbert spaces: nonasymptotic confidence balls
Online estimation of the asymptotic variance for averaged stochastic gradient algorithms
Nonlinear least-squares estimation
Clustering time series gene expression data based on sum-of-exponentials fitting
Optimal non-asymptotic analysis of the Ruppert-Polyak averaging stochastic algorithm
Efficient training of neural nets for nonlinear adaptive filtering using a recursive Levenberg-Marquardt algorithm
Adaptivity of averaged stochastic gradient descent to local strong convexity for logistic regression
Acceleration of Stochastic Approximation by Averaging
Asymptotic Almost Sure Efficiency of Averaged Stochastic Algorithms
RES: Regularized Stochastic BFGS Algorithm
An Efficient Stochastic Newton Algorithm for Parameter Estimation in Logistic Regressions
Applications of Regression Models in Epidemiology
Asymptotic Properties of Non-Linear Least Squares Estimators
Adjustment of an Inverse Matrix Corresponding to a Change in One Element of a Given Matrix
A Stochastic Approximation Method
L^p and almost sure rates of convergence of averaged stochastic gradient algorithms: locally strongly convex objective

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