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Questions tagged [stochastic-approximation]

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Phase space Brownian bridge

I understand the concept of the 1 dimensional Brownian bridge with the form of: $$dx_t=\frac{-1}{1-t}x_t \, dt + dw_t$$ s.t. $x_0=0$ and $x_1=0$ where $dw_t$ is a Wiener process. I am thinking about ...
BayesFans's user avatar
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Recursive formula for approximate multiple Wiener integrals

Given $m$ $d$-dimensional Brownian motion and a multi-index $(j_1,...,j_l)$ with $j_i \in \{0,1,...,m\}$ we can define the multiple Stratonovich integral $\int_0^t \circ dW_{s_1}^{j_1}...\int_0^{s_{l-...
Marco's user avatar
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Finding the limit of a specific sequence of linear processes

Given a strictly stationary random process $(\xi_t)_{t \in \mathbb Z}$. Define $\mu:= E[\xi_t]$, for all $t$. Suppose $(\xi_t)_{t \in \mathbb Z}$ ergodic: \begin{equation}\label{a}\tag{E} \frac{1}{n}\...
Fam's user avatar
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Understanding the approximation of a random sum of random processes

I want to understand an approximation of a compound Poisson distribution in this paper. First, let's set the environment. Consider $\mathcal{P}$ the class of distributions of real-valued and strictly ...
Fam's user avatar
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A double sum with complex numbers having stochastic variables

I am very confused by a sum I have been trying to solve analytically/ numerically for a long time. It comes from the idea of a physical problem where the observation is made that has a combined ...
CfourPiO's user avatar
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Adiabatic elimination of "fast"/"velocity" variable

My question comes from section IV, part A of the paper titled Stochastic resonance. Specifically, their equation (4.1) states that, if we start with a Langevin equation of the form $$m\ddot{x} = -m\...
Math and YuGiOh lover's user avatar
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A semimartingale interpolation problem

This question is a direct extension of this one. Let $(\Omega,\mathcal{F},(\mathcal{F}_t)_{t\geq 0},\mathbb{P})$ be a stochastic basis and let $N\in\mathbb{Z}^+$, $T>0$, $\{t_n\}_{n=1}^{N}$ be a ...
Joe_Affine's user avatar
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A martingale extension/interpolation problem

Let $(\Omega,\mathcal{F},(\mathcal{F}_t)_{t\geq 0},\mathbb{P})$ be a stochastic basis and let $N\in\mathbb{Z}^+$, $T>0$, $\{t_n\}_{n=1}^{N}$ be a partition of $[0,T]$ with $t_0=0,t_n<t_{n+1},t_N=...
Joe_Affine's user avatar
2 votes
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The stochastic approximation algorithm of Robbins-Monro

I am reading A Stochastic Approximation Method by Herbert Robbins and Sutton Monro and have a question concerning their algorithm. In below, I will basically follow their construction but will change ...
No One's user avatar
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Applications of products of random matrices

I'm studying the paper "Matrix concentration for products" and I'm trying to find simple applications of the inequalities for the expected value of the spectral norm of products of random ...
Florian Ente's user avatar
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Minimizing $\int\lambda({\rm d}y)\frac{\left|g(y)-\frac{p(y)}c\lambda g\right|^2}{r((i,x),y)}$ with respect to discrete parameter $i$

Let $I\subseteq\mathbb N$ be finite and nonempty, $(E,\mathcal E,\lambda)$ be a $\sigma$-finite measure space, $$\lambda f:=\int f\:{\rm d}\lambda$$ for $\lambda$-integrable $f:E\to\mathbb R$, $p:E\to(...
0xbadf00d's user avatar
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Reference for the positive probability of convergence to a stable point of a stochastic approximation algorithm

Consider a stochastic approximation process with $$x_{t+1} = x_t + \frac{1}{t} (g(x_t)+u_t)$$ where $(u_s)_s$ is a sequence of i.i.d. shocks. Assume $g$ is Lipschitz, $u_t$ has finite variance, and ...
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