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Confidence Regions for Stochastic Approximation Algorithms
Confidence Regions Stochastic Approximation Algorithms
2015/7/8
In principle, known central limit theorems for stochastic approximation schemes permit the simulationist to provide confidence regions for both the optimum and optimizer of a stochastic optimization p...
Analysis of a Stochastic Approximation Algorithm for Computing Quasi-stationary Distributions
Stochastic approximations quasi-stationary distribution ODE method.
2015/7/6
This paper analyzes the convergence properties of an iterative Monte Carlo procedure proposed in the Physics literature for estimating the quasi-stationary distribution on a transient set of a Markov ...
Almost sure convergence and asymptotical normality of a generalization of Kesten's stochastic approximation algorithm for multidimensional case
Kesten's stochastic approximation algorithm multidimensional
2011/6/20
It is shown the almost sure convergence and asymptotical normality of a generalization of
Kesten's stochastic approximation algorithm for multidimensional case.
In this generalization, the step incr...
Stochastic Approximation and Newton's Estimate of a Mixing Distribution
Stochastic approximation empirical Bayes mixture models Lyapunov functions
2011/3/23
Many statistical problems involve mixture models and the need for computationally efficient methods to estimate the mixing distribution has increased dramatically in recent years. Newton [Sankhya Ser....
Stochastic Approximation and Newton's Estimate of a Mixing Distribution
Stochastic approximation empirical Bayes mixture models Lyapunov functions
2011/3/22
Many statistical problems involve mixture models and the need for computationally efficient methods to estimate the mixing distribution has increased dramatically in recent years. Newton [Sankhya Ser....
Construction of Bayesian Deformable Models via Stochastic Approximation Algorithm：A Convergence Study
stochastic approximation algorithms non rigid-deformable templates shapes statistics Bayesian modeling MAP estimation
2010/4/29
The problem of the definition and the estimation of generative models based on deformable templates from raw data is of particular importance for modeling non-aligned data affected by various types of...
Semimartingale Stochastic Approximation Procedures and Recursive Estimation
Stochastic approximation Robbins–Monro type SDE semimartingale convergence sets “standard” and “nonstandard” representations
2010/4/29
The semimartingale stochastic approximation procedure, namely,
the Robbins–Monro type SDE is introduced which naturally includes
both generalized stochastic approximation algorithms with martingale ...