
NonAsymptotic Analysis of Stochastic Approximation Algorithms for Streaming Data
Motivated by the highfrequency data streams continuously generated, rea...
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Convergence in quadratic mean of averaged stochastic gradient algorithms without strong convexity nor bounded gradient
Online averaged stochastic gradient algorithms are more and more studied...
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On the asymptotic rate of convergence of Stochastic Newton algorithms and their Weighted Averaged versions
The majority of machine learning methods can be regarded as the minimiza...
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An efficient Averaged Stochastic GaussNewton algorithm for estimating parameters of non linear regressions models
Non linear regression models are a standard tool for modeling real pheno...
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An efficient Averaged Stochastic GaussNewtwon algorithm for estimating parameters of non linear regressions models
Non linear regression models are a standard tool for modeling real pheno...
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An efficient stochastic Newton algorithm for parameter estimation in logistic regressions
Logistic regression is a wellknown statistical model which is commonly ...
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On the rates of convergence of Parallelized Averaged Stochastic Gradient Algorithms
The growing interest for high dimensional and functional data analysis l...
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Antoine GodichonBaggioni
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