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Can conditional distributions with respect to a sufficient sub-$\sigma$-algebra be represented by a single Markov kernel?

Let $(\Omega, \mathcal{F})$ be a measurable space, and let $\mathcal{P}$ be a collection of probability measures on this space. A sub-$\sigma$-algebra $\mathcal{G} \subset \mathcal{F}$ is said to be ...
MrTheOwl's user avatar
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0 answers
48 views

Quantile maximization of the difference of random constrained quadratic optimization problems

I am interested in understanding the family of parametrized random variables defined by the pushforward map $$ \lambda_x : \varepsilon \mapsto \underset{z_1 \in \mathbb{R}^n :\, h^T z_1 = 0, \; z_1 \...
NeyPea's user avatar
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0 answers
61 views

Bound on $\int_0^1\sqrt{\log N_{[]}(\varepsilon,\mathcal{F},d)} \, d\varepsilon$ over the class of half-spaces $\mathcal{F}$ on $\mathbb{R}^d$?

For a class of functions $\mathcal{F}$ and a pair $f,g\in\mathcal{F}$ with $f\leq g$, the interval $[f,g]=\{h:f(x)\leq h(x)\leq g(x),\forall x\in\mathbb{R}^d\}$ is called a bracket for $\mathcal{F}$. ...
Daan's user avatar
  • 141
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44 views

Constrained random sampling from partitioned sets with quotas

Let $D$ be a finite set, $\mathcal{P} = \{D_{i,j}\}_{(i,j) \in I \times J}$ a partition of $D$, $N: J \to \mathbb{N}$ a quota function, and $k \in \mathbb{N}^+$. A subset $F \subseteq D$ is considered ...
DataGuy553's user avatar
1 vote
0 answers
80 views

Moments from characteristic function for matrices

When $x$ is a random variable with the smooth characteristic function $\phi_x(t) = \mathbb{E}e^{itx}$, we can easily compute the moments as $\mathbb{E}[x^k] = i^{-n}\phi_x^{(n)}(0)$. There is no magic ...
user3826143's user avatar
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0 answers
53 views

The limit ratio of two Markov Chain Probability

Suppose there are two given SDE in $\mathbb{R}^d$: $$ \begin{align} \left\{ \begin{aligned} dX_t&=\begin{bmatrix}-\nabla V(X_t)+2\beta^{-1}v_F^\theta(X_t)\end{bmatrix}dt+\sqrt{2\beta^{-1}}dW_t,&...
Francis Fan's user avatar
1 vote
0 answers
68 views

Gibbs Priors form a Martingale

I am working on adapting variational inference to the recently developed Martingale posterior distributions. The first case, which reduces the VI framework to Gibbs priors, is proving hard to show as ...
BayesRayes's user avatar
1 vote
1 answer
241 views

Expectation of top-K selection of squared Gaussian random variables

Let us have $$ Z = [z_1, z_2, \dots, z_n], $$ where $z_i \sim N(0, \sigma^2)$ and are iid. Additionally, consider $$ X_k := \{ x \in \{0, 1\}^n : e^T x = k \} $$ If $Y = \max_{X \in X_k} |Z^T X|^2,$ ...
Alireza Khayatian's user avatar
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62 views

A small lemma on cache resets (Bloom filters in particular)

Assume a fixed set of message $D$ and an associated distribution for selecting each message $d_i$ such that the total probability $\sum_{i \in D} d_i = 1$. We create a cache with $M$ bits and $k$ ...
Birdy Nam Nam's user avatar
1 vote
0 answers
72 views

Dimension-free sample complexity for the inverse of Gaussian sample covariance?

Suppose I have $m$ samples drawn from a Gaussian in $\mathbb{R}^n$, and need the inverse of the sample covariance $\Sigma_m^{-1}$ to be $\varepsilon$-close to true inverse covariance $\Sigma^{-1}$ (in ...
axk's user avatar
  • 517
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0 answers
148 views

conjecture for general form of minimax estimator

I had previously posed an overly ambitious version of this conjecture here, Form of minimax estimator, which was quickly shot down by Václav Voráček (on twitter) and Iosif Pinelis (MO answer in the ...
Aryeh Kontorovich's user avatar
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0 answers
57 views

Limiting value of expectation of trace of truncated Gram matrix

Let $n$ and $d$ be large positive integers such that $d/n = a \in (0,1)$, fixed. Let $x_1,\ldots,x_n$ be iid random vectors from $N(0,I_d)$. Fix $b \in (0,1]$ and a unit-vector $v \in \mathbb R^d$, ...
dohmatob's user avatar
  • 6,853
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0 answers
67 views

Random matrix theory: accounting for mean

Assume a random matrix, denoted as $X$, which is an $n$ by $T$ matrix, $T\geq n$. While I understand the typical scenario where the random variables $X_{ij}$ are sampled from a $\mathcal{N}(0,\sigma_{...
Pooja Algikar's user avatar
1 vote
0 answers
112 views

A high probability bound for a Rademacher process

Let $\{x_i(t)\}_{i=1}^n$ be i.i.d. Gaussian processes for $t \in [0, T]$ with \begin{align*} \mathbb{E}[x_i(t)] & = 0, \quad \forall i \in [1 : n], \ t \in [0, T] \\ \mathbb{E}[x_i(s) x_i(t)] &...
fs l's user avatar
  • 81
1 vote
0 answers
144 views

Estimator for the conditional expectation operator with convergence rate in operator norm

Let $X$ and $Z$ be two random variables defined on the same probability space, taking values in euclidian spaces $E_X$ and $E_Z$, with distributions $\pi$ and $\nu$, respectively. Let $L^2(\pi)$ ...
Caio Lins's user avatar
  • 111
1 vote
1 answer
69 views

Expected value of MGIG distribution

I'm currently dealing with a Gibbs sampler of the multivariate generalized inverse Gaussian distribution (MGIG). In order to check the correctness of the sampler, I'd like to know the expected value ...
Stéphane Laurent's user avatar
1 vote
0 answers
39 views

Characteristic function of a Dirichlet Process

Suppose $P \sim \text{DP}(\alpha,G) $ where $G \sim N(0,1)$ is the base measure and $\alpha > 0$ is the concentration parameter. The stick breaking representation says that $P$ can be expressed as \...
Zilch's user avatar
  • 11
1 vote
0 answers
68 views

Limiting value of expectation of $\operatorname{tr}(BR(z))$, where $R(z) := (X^\top X - z I_d)^{-1}$ and $X \sim N_{n,d}(0,A)$

Let $A=A(d)$, and $B=B(d)$ be (sequences of) deterministic positive-definite $d \times d$ matrices and let $X$ be an $n \times d$ random matrix with iid rows from $N(0,A)$. Let $R$ be the resolvent of ...
dohmatob's user avatar
  • 6,853
1 vote
0 answers
124 views

Using projections to determine equidistribution

Suppose I have a collection of points on $\mathbb{S}^{n-1} \subset \mathbb{R}^n.$ I want to know that they are equidistributed (if you want to be more precise, you have a sequence of such collections, ...
Igor Rivin's user avatar
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1 vote
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48 views

Sample complexity of estimating a doubly stochastic matrix

Let $P\in\mathbb{R}^{n\times n}$ be a doubly-stochastic matrix. That is: $$P(x,y)\geq 0,\quad \sum_xP(x,y)=1,\quad \sum_yP(x,y)=1.$$ I would like to know if lower and upper bounds on the sample ...
user134977's user avatar
1 vote
0 answers
24 views

Minimax statistical estimation of proximal transform $\mbox{prox}_g(\theta_0)$, from linear model data $y_i := x_i^\top \theta_0 + \epsilon_i$

tl;dr: My question pertains the subject of minimax estimation theory (mathematical statistics), in the context of linear regression. Given a vector $\theta_0 \in \mathbb R^d$, consider the linear ...
dohmatob's user avatar
  • 6,853
1 vote
0 answers
82 views

Concavity of expected size of a maximum matching (in a bipartite graph) w.r.t. edge probability

Given a n*n bipartite graph where each edge (between any two nodes on the opposite side) is formed i.i.d. with probability $p$, can we show a concavity result on the expected size of a maximum ...
messi22's user avatar
  • 53
1 vote
0 answers
59 views

How to calculate the unifrom entropy or VC dimension of the following class of functions?

When dealing with U process I meet with such a uniform entropy to calculate. For any $\eta>0$, function class $\mathcal{F}$ containing functions $f=\left(f_{i, j}\right)_{1 \leq i \neq j \leq n}: \...
leslie zhang's user avatar
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0 answers
83 views

Properties of max of many linear combinations of a multivariate normal vector and/or sum of top $k$ elements of a multivariate normal vector

Thank you in advance for your help! I am interested in studying the following probability: $$P\big[\max_{H \subset X,|H|=k} \sum_{i \in H} \mathbf{a}_i^T \mathbf{w} \ge 0 \big],$$ where $\mathbf{a}_i$ ...
Vergil's user avatar
  • 11
1 vote
1 answer
153 views

Minimax estimation rate of sparse vector $w_\star$, w.r.t to mixed norm $\|\hat w_n-w_\star\| := \|\hat w_n - w_\star\|_2 + \|\hat w_n-w_\star\|_q$

Let $n,d,s$ be positive integers with $s \le d$, and let $B_0(d,s)$ be the set of all (real) $d$-dimensional vectors with at most $s$ nonzero components. Given an $n \times d$ matrix $X$ with rows $...
dohmatob's user avatar
  • 6,853
1 vote
0 answers
417 views

Conditions for equivalence of RKHS norm and $L^2(P)$ norm

Let $K$ be a psd kernel on an abstract space $X$ and let $H_K$ be the induced Reproducing Kernel Hilbert Space (RKHS). Let $P$ be a probability measure on $X$ such that $H_K \subseteq L^2(P_X)$ and ...
dohmatob's user avatar
  • 6,853
1 vote
0 answers
100 views

$L_1$ convergence rates for multivariate kernel density estimation

Let $X$ be a random variable on $\mathbb R^d$ with probability density function $f$, and let $X_1,\ldots,X_n$ of $X$ be $n$ iid copies of $X$. Given a bandwidth parameter $h=h_n > 0$ and a kernel $...
dohmatob's user avatar
  • 6,853
1 vote
0 answers
146 views

Using maximum entropy principle for joint probability estimation

Let $X_1, \dots, X_n, Y$ be random variables, each taking values in $\{0,1\}$. Assume that we are interested in estimating, for each $v=(v_1,\dots,v_n)\in \{0,1\}^n$, the probability $$ p(v) = P[Y=1|...
Bogdan Grechuk's user avatar
1 vote
1 answer
160 views

Given iid $w_1,\dotsc,w_N \sim N(0,1/d)$ iid, find a simple matrix $A$ s.t $\|aa^T-A\|_\text{op}\to0$, where $a_i := E_{G \sim N(0,1)}[f(\|w_i\| G)]$

Let $d$ and $N$ be two large comparable integers, for example assume $$ N,d \to \infty, \quad d/N \to \gamma \in (0,\infty). $$ Let $w_1,\dotsc,w_N$ be iid from $N(0,(1/d)I_d)$ and let $f:\mathbb R \...
dohmatob's user avatar
  • 6,853
1 vote
0 answers
78 views

Canonical representation of the a probability distribution for Hammersley Clifford Theorem

I'm reading the following paper http://www2.stat.duke.edu/~scs/Courses/Stat376/Papers/GibbsFieldEst/BesagJRSSB1974.pdf On page 7 they give the result that $$Q(\textbf{x}) = \sum_{1 \leq i \leq n} ...
Pavan Sangha's user avatar
1 vote
0 answers
349 views

Tail bounds for random Gaussian chaos?

Let $g = (g_1, \dots, g_d)$ be a sequence of independent standard Normal random variables, and suppose $\Sigma$ is a $d \times d$ (deterministic), real, symmetric, positive definite matrix. The Hanson-...
Drew Brady's user avatar
1 vote
1 answer
415 views

Approximate the singular values of a certain random dot-product kernel matrix (in the sense of El Karoui, Cheng-Singer, etc.)

Let $g:\mathbb R \to \mathbb R $ be a continuous function which is "sufficiently smooth" (e.g $\mathcal C^3$) around $0$, and "sufficiently integrable" (e.g integrable w.r.t $N(0,...
dohmatob's user avatar
  • 6,853
1 vote
0 answers
45 views

Is there a local limit theorem for functions of Gaussian random vectors?

Assume that $\sqrt{n} (\boldsymbol{Z}_n - \boldsymbol{\mu}) \stackrel{\mathcal{D}}{\longrightarrow} \mathcal{N}(\boldsymbol{0},\Sigma)$, as $n\to \infty$, for some $\boldsymbol{\mu}\in \mathbb{R}^d$ ...
Aftermath 12345's user avatar
1 vote
0 answers
198 views

Weak convergence of Cesaro means of weakly converging infinite-dimensional distribution

Suppose we have sequences of random variables $\{X_{n,m},n \in \mathbb{N}\}$ where the distribution of $(X_{n,m})_{n\in\mathbb{N}}$ converges weakly to an infinite-dimensional normal distribution $\...
moe.dancer's user avatar
1 vote
0 answers
489 views

Can we generalize the concept of "characters" in group theory via methods from statistics and probability theory?

$\DeclareMathOperator\Cov{Cov}$Motivation: If $G$ is a finite group and $\phi=X+iY: G\to \mathbb{T}$ is a character of $G$, then $\Cov(X,Y)=0$ where $X$, $Y$ are considered as two real random ...
Ali Taghavi's user avatar
1 vote
0 answers
233 views

Variance-based localized Rademacher complexity for RKHS unit-ball

Let $\mathscr X$ be a compact subset of $\mathbb R^d$ (e.g the unit-sphere). Let $K: \mathscr X \times \mathscr X \to \mathbb R$ be a positive kernel function and let $\mathscr H_K$ be the induced ...
dohmatob's user avatar
  • 6,853
1 vote
0 answers
75 views

Percentile interval Lemma

Let $\theta$ be a parameter and $\hat{\theta}$ the plug-in estimate, I need a proof of the following lemma, as given in [1], p. 173, in the form of a reference or of a direct argument: Percentile ...
Roberto Palermo's user avatar
1 vote
0 answers
65 views

Normalizing constants preserve metric entropy

Suppose $\mathcal{F}=\left\{f\in L^2([a,b]): 0<\underline{c}\leq f\leq\overline{c} \right\}$. Consider the following transformation $$\tilde{\mathcal{F}} := \left\{\frac{f}{\int f d\mu}: f\in \...
lucaszz's user avatar
  • 11
1 vote
0 answers
42 views

Estimation of a density by orthogonal projection

I was wandering if the following problem was already treated in the litterature. Suppose i want to estimate a density $f$ by an estimator $\hat{f}$ that i cannot explicitely describe. All i have is ...
lrnv's user avatar
  • 686
1 vote
0 answers
68 views

(Anti-)concentration of gap between largest and second largest component of multivariate random gaussian vector

Let $n$ be a large positive integer and let $Y=(Y_1,\ldots,Y_n)$ be a zero-centered random $n$-dmensional real vector with covariance matrix $\Sigma$, an $n$-by-$n$ positive definite matrix with ...
dohmatob's user avatar
  • 6,853
1 vote
0 answers
49 views

semi-parametric regression

Suppose the observation $(X_1, Y_1), \ldots, (X_n, Y_n)$ satisfies the following semi-parametric model $$Y_t = m(X_t, \alpha) + \sigma(X_t, \beta) U_t,$$ where $U_t$ is independent with $X_t$ with ...
香结丁's user avatar
  • 331
1 vote
0 answers
99 views

Covering number after projection

In these lecture notes on Statistical Learning Theory we find the following definitions for covering numbers: Definition. Let $(\mathcal{W}, d)$ be a metric space and $\mathcal{F} \subset \mathcal{W}$...
Jonas Metzger's user avatar
1 vote
0 answers
35 views

The asymptotic properties of $V$-statistic for mixing multivariate process

Suppose $\{X_t\}_{t \in \mathbb{Z}} \subseteq \mathbb{R}^d$ is a $\alpha$- or $\rho$-mixing process. Let $h (x, y) : \mathbb{R}^d \times \mathbb{R}^d \rightarrow \mathbb{R}$ be the symmetric kernel ...
香结丁's user avatar
  • 331
1 vote
0 answers
146 views

Bounding the probability of success of adding elements into a list

Suppose $𝐿_1,…,𝐿_𝑘$ are lists with $n$ elements each. We use a fully independent hash function ℎ to compute a value for each element of each list. (We suppose the hash function returns a value ...
user1246462's user avatar
1 vote
0 answers
177 views

Probability of satisfying the congruent mod equation

I'm wondering about the probability of picking three different numbers $x,y,z$ out of the set $[50]=\left\{ 1,2,3,...,50\right\}$ satisfying the equation: $$xyz\equiv \gcd(x,y,z)\mod 7$$ I started out ...
Marek Kryspin's user avatar
1 vote
0 answers
46 views

How to use the mixed normal distribution to construct a proper statistics?

For a random vector $\xi_n \in \mathbb{R}^p$, if $\xi_n \rightarrow_d N(\mu, \Sigma)$, we can construct \begin{equation*} \Psi := \xi_n^{\top} \widehat{\Sigma}^{-1} \xi_n \end{equation*} for ...
香结丁's user avatar
  • 331
1 vote
0 answers
212 views

A new notion of probability coupling

Let $X$ and $Y$ be two discrete random variables distributed according to $\mu$ and $\nu$, respectively. Consider the following optimization problems $$\inf_{\pi\in \Pi(\mu, \nu)}\Pr(X\neq Y),$$ ...
math-Student's user avatar
  • 1,109
1 vote
0 answers
131 views

Almost sure stochastic equicontinuity

Suppose $\mathcal{G}$ is a normed closed class of functions with finite entropy and envelope with a finite second moment (details below), and $g_0$ is a function in the interior of that class. Let $...
Caetano's user avatar
  • 59
1 vote
0 answers
64 views

Dependence rank: what is the size of the largest subcollection of random variables which is statistically independent?

Let $X_1,\ldots,X_p$ be random variables on the same space. Define their dependence rank, denoted $rank(X_1,\ldots,X_p)$ as the largest nonnegative integer $k$ such that there is a subcollection of $k$...
dohmatob's user avatar
  • 6,853
1 vote
0 answers
45 views

What is the number of iterations needed for the message passing algorithm to converge when applied to an acyclic factor graph?

I understand that the message passing algorithm (Belief Propagation algorithm), when applied to a factor graph consists in an exchange in messages between the factor nodes and the variable nodes, ...
e. sfe's user avatar
  • 39

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