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Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Stochastic approximation methods for nonconvex constrained optimization
非凸 约束优化 随机逼近方法
2023/4/14
Nonconvex constrained optimization (NCO) has been one of the important research fields in optimization community. It has widely appeared in many application fields. However, challenges for solving NCO...
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....
Trajectory averaging for stochastic approximation MCMC algorithms
Trajectory averaging MCMC algorithms
2010/11/18
The subject of stochastic approximation was founded by Robbins and Monro [Ann. Math. Statist. 22 (1951) 400--407]. After five decades of continual development, it has developed into an important area...
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...
STOCHASTIC APPROXIMATION IN REAL TIME:A PIPE LINE APPROACH
STOCHASTIC APPROXIMATION IN REAL TIME:A PIPE LINE APPROACH
2007/12/10
A new approach for stochastic approximation in real time is developed. A number of processors are simultaneously active to carry out a computing task. All processors work on the same system with diffe...
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 ...