https://devthrottle.com/ai-library/papers/robbins-monro-stochastic-approximation
A Stochastic Approximation Method - The AI Library | DevThrottle
Robbins and Monro's 1951 paper introducing stochastic approximation, the mathematical ancestor of stochastic gradient descent.
stochastic approximationmethodlibrary
https://oa.tib.eu/renate/items/f55a596e-d140-4489-80d1-8f93946bd2d7
Stochastic approximation versus sample average approximation for Wasserstein barycenters
In the machine learning and optimization community, there are two main approaches for the convex risk minimization problem, namely the Stochastic Approximation...
stochastic approximationsample averageversuswassersteinbarycenters
https://arxiv.org/abs/2411.12995v2
[2411.12995v2] Beyond likelihood ratio bias: Nested multi-time-scale stochastic approximation for...
Abstract page for arXiv paper 2411.12995v2: Beyond likelihood ratio bias: Nested multi-time-scale stochastic approximation for likelihood-free parameter...
likelihood ratiotime scalestochastic approximationbeyondbias
https://bmj.chnu.edu.ua/en/issuances/scientific-bulletin-of-chnu-mathematics-series-volume-2-no-2-3-2012/convergence-of-the-stochastic-approximation-procedure-in-the-asymptotically-small-diffusion-scheme/
Convergence of the stochastic approximation procedure in the asymptotically small diffusion scheme
O.I. Kiykovska, YA.M. Chabanyuk article Convergence of the stochastic approximation procedure in the asymptotically small diffusion scheme
of thestochastic approximationconvergenceprocedureasymptotically
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https://optimization-online.org/2025/07/stochastic-approximation-with-block-coordinate-optimal-stepsizes/
Stochastic Approximation with Block Coordinate Optimal Stepsizes – Optimization Online
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https://simons.berkeley.edu/talks/tutorial-finite-sample-guarantees-contractive-stochastic-approximation-applications-0
A Tutorial on Finite-Sample Guarantees of Contractive Stochastic Approximation With Applications in...
Reinforcement learning (RL) is a learning paradigm for large-scale sequential decision making problems in complex stochastic systems. Many modern RL algorithms...
a tutorialstochastic approximationfinitesampleguarantees
https://dblp.org/rec/conf/valuetools/BianchiJ11.html
dblp: Distributed stochastic approximation for constrained and unconstrained optimization.
Bibliographic details on "Distributed stochastic approximation for constrained and unconstrained optimization."
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https://tomesphere.com/paper/1803.08593
Stochastic and variational approach to finite difference approximation of Hamilton-Jacobi equations...
Mar 26, 2018 - This paper extends a stochastic variational finite difference scheme for Hamilton-Jacobi equations to higher dimensions, demonstrating stability, convergence,...
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https://strathprints.strath.ac.uk/85872/
On approximation of solutions of stochastic delay differential equations via randomized Euler...
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