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5 votes
2 answers
679 views

distance in terms of the variance between two absolutely continuous probability measures

Consider two probability measures $\mu_0$ and $\mu_1$ on $\mathbb{R}^n$, such that $\mu_0\ll \mu_1$. Then I can define a "distance" like quantitiy $$ \mathrm{Var}_{\mu_1}\left(\frac{\mathrm{d}\mu_0}{\...
3 votes
2 answers
1k views

A general inequality for KL divergence of functions of variables

The question concerns a very general setting and a very general inequality about KL divergence. I'm writing this thread to verify whether my intuition is correct. Let $E_1, E_2$ be two measurable ...
1 vote
1 answer
135 views

KL-divergence and sub-$\sigma$-algebras

I am trying to understand if the following claim is true: Let $P$, $Q$ be probability measures on $\mathcal{X}$. For any $\sigma$-algebra $\mathcal{G}$, with countably many atoms (sets with $\...
2 votes
1 answer
181 views

Conditional entropy - solve example

Given a random variable $X$ that is uniformly distributed on $[-b,b]$ and $Y=g(X)$ with $$g(x) = \begin{cases} 0, ~~~ x\in [-c,c] \\ x, ~~~ \text{else}\end{cases}$$ Now I want to compute the ...
2 votes
1 answer
294 views

Information theory for uncountably infinite-dimensional continuous random variable

I'm exploring the possibility to apply information theory on an uncountably infinite-dimensional scenario. I found the concept of generalized entropy for continuous random variables defined on finite-...
1 vote
0 answers
184 views

Bounding the total variation metric between Gaussian mixtures

Let $\mathcal{P}(\mathbb{R}^d)$ the space of probability measures on $\mathbb{R}^d$ with total variation metric $\delta$, fix $k \in \mathbb{N}$, and let $\mathcal{P}'\subset \mathcal{P}(\mathbb{R}^d)$...
8 votes
1 answer
355 views

Lower Bound of KL-Divergence Between Two Gibbs Measures

Suppose we have two Gibbs measures with densities $$ p_f(x) \propto \exp(f(x)),\quad q_g(x)\propto \exp(g(x)). $$ Consider the KL-divergence between $p_f$ and $q_g$, as a functional of $f$ and $g$, ...
4 votes
1 answer
352 views

Measure of the rate of convergence for filtration and conditional expectations

This question is cross-posted at MSE with a soon to expire bounty that hasn't generated much discussion. Let $(\Omega, \mathcal{F},P)$ be a probability space and $(\mathcal{F}_n)_n$ a filtration that ...
3 votes
0 answers
428 views

When is the entropy of a $\sigma$-algebra finite?

Let two (countably-generated) $\sigma-$algebras $\mathscr{F,G}$ on the event space $\mathbb{R}$ be given. I believe we also need the atoms of $\mathscr{F,G}$ to be the points of $\mathbb{R}$. Let $\...
5 votes
0 answers
137 views

Large Deviations: Exponential decay in normed spaces

Let $(X_1,X_2,\cdots)$ be a sequence of independent and identically distributed random variables taking values in some general normed space $(V,||\cdot||)$. Denote $\mu=E[X_1]$ and $S_n=\frac{1}{n}[...
9 votes
0 answers
223 views

Cramer's theorem in Hilbert spaces

I am interested under what conditions Cramer's theorem applies in random variables taking values in Hilbert spaces. Following these lecture notes, but using a Hilbert space: Let $X_1,X_2,\cdots$, be ...
3 votes
0 answers
133 views

What distribution(s) of delays make(s) timing attacks hardest?

$H$ is (Shannon) entropy. In terms of the positive real number $t$, what distribution(s) $\hspace{.01 in}X$ on $\:[0\hspace{.005 in},\hspace{-0.03 in}\scriptsize+\normalsize\infty\hspace{-0.02 in})$...
15 votes
3 answers
3k views

Entropy of a measure

Let $\mu$ be a probability measure on a set of $n$ elements and let $p_i$ be the measure of the $i$-th element. Its Shannon entropy is defined by $$ E(\mu)=-\sum_{i=1}^np_i\log(p_i) $$ with the ...
10 votes
2 answers
1k views

Continuity of the mutual information

The mutual information $I(\mathfrak A_1;\mathfrak A_2)$ of two complete $\sigma$-algebras $\mathfrak A_1$ and $\mathfrak A_2$ in a Lebesgue probability space $(X,m)$ is the integral of the logarithm ...