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What are examples of $\epsilon$-extractable uniform randomness $H_{\rm ext}^\epsilon(\cal P)$?

[Renner and Wolf 2004] introduces the notion of $\epsilon$-smooth Renyi entropies as $$H_\alpha^\epsilon(P) \equiv \frac{1}{1-\alpha} \inf_{Q\in \mathcal B^\epsilon(P)}\log\left(\sum_z Q(z)^\alpha\...
glS's user avatar
  • 342
1 vote
1 answer
163 views

trying to get intuition into why Cross Entropy will always be greater or equal to the Entropy

I understand what entropy measures and cross entropy is the same except it is uses another distribution $q$ to compare it against $p.$ Is it because the log function is concave down so the predictions ...
Chris Blodgett's user avatar
0 votes
0 answers
179 views

About the monotonicity of the exponential entropy

This question was previously posted on MSE at About the monotonicity of the exponential entropy. In the paper The Unifying Frameworks of Information Measures the conditional exponential entropy (see ...
Upax's user avatar
  • 127
2 votes
0 answers
120 views

Information inequality for Renyi divergences

Let $X^1 \ldots X^n$ be random variables on $\mathbb{R}^d$ with an arbitrary joint probability distribution $\mu$ on $\mathbb{R}^{n \times d}$. Let $\nu = \nu^1 \times \ldots \times \nu^n$ be a ...
MatrixGeek1234's user avatar
1 vote
1 answer
182 views

Inequalities involving entropy: quantum discord and mutual information

My question is inspired by the following paper of Olivier and Żurek but for this question to be self-contained I will recall all the necessary definitions: for a quantum state $\rho$ we define the ...
truebaran's user avatar
  • 9,330
0 votes
0 answers
85 views

Does there exist an established name for the exponential of surprisal (e.g. the reciprocal of probability?)

There are several different names that I know of for the exponential of the entropy of which "diversity" and "perplexity" are fairly well-established. Tom Leinster has a very ...
Mike Battaglia's user avatar
3 votes
1 answer
205 views

Bound on an integral representing a difference of two relative entropies

Let $ f : [0,1] \to \mathbb{R} $ be a function satisfying: 1.) $ |f(x)| \leqslant a $ for some $ a < 1 $, and 2.) $ \int_0^1 f(x) {\mathrm d}x = 0 $. I would like to know whether the following ...
aleph's user avatar
  • 503
8 votes
1 answer
314 views

Lower bound $\int_0^1 \frac{|f'(x)|^2}{f} \,\mathrm{d} x$ by $\int_0^1 |f-1|^2\, \mathrm{d} x$

Assume that $f$ is a probability density on $x \in (0,1)$, I want to obtain a bound of the following form (if it is possible at all): $$ \int_0^1 \frac{|f'|^2}{f} \,\mathrm{d} x \geq C\,\int_0^1 |f-1|^...
Fei Cao's user avatar
  • 730
3 votes
1 answer
127 views

Conditions for: (local) lipschitz stability of I-projection

The following post builds on this post; I'll begin by quoting the setting. Background from Previous Question: $\newcommand\SS{P}\newcommand\TT{Q}$Call a Gaussian probability measure $\SS$ on $\mathbb{...
Math_Newbie's user avatar
1 vote
1 answer
124 views

References: error and stability estimates for information projection

$\newcommand\SS{P}\newcommand\TT{Q}$I will call a Gaussian probability measure $\SS$ on $\mathbb{R}^d$ isotropic if its covariance matrix is diagonal with non-vanishing determinant; i.e. $\Sigma_{i,i}&...
Math_Newbie's user avatar
3 votes
1 answer
211 views

Entropy of $f^{m(x)+n}$ of full shift

Let $(X,\mu,f)$ be a two-sided full shift system. Assume that there is $t \in \mathbb{N}$ such that for every $n \in \mathbb{N}$ and $x \in X$, we can define $T(x)=f^{n+m(x)}(x)$, where $m(x) \leq t; $...
Adam's user avatar
  • 1,043
2 votes
0 answers
111 views

Generalization of the min-entropy that looks at the top $n$ probabilities

The min-entropy of a random variable $X$ can often be much easier to compute than the Shannon entropy. This is because the min-entropy is simply a function of the most probable value, and sometimes, ...
Mike Battaglia's user avatar
15 votes
1 answer
703 views

Information inequalities

What are the feasible $2^n$-tuples of entropies $h(S) := H(X_{i_1},\dots,X_{i_{|S|}})$ where $X_1,\dots,X_n$ are discrete random variables with some (unknown) joint probability distribution as $S=\{...
James Propp's user avatar
  • 19.7k
2 votes
0 answers
142 views

List decodability of Reed-Solomon codes beyond the Johnson bound

In a paper on a proximity test for Reed-Solomon codes the authors state an "extremely optimistical" conjecture on the list decodability of Reed-Solomon codes (over prime fields $\mathbb F_q$)...
U. Haboeck's user avatar
4 votes
1 answer
330 views

Bipartite version of Hamming bound (two families of codewords with large Hamming distance)?

Update: In light of Fedor Petrov's answer, I added an additional requirement that all strings in $A$ and $B$ have Hamming weight exactly $n/2$, which hopefully makes the question more interesting. ...
Octopus's user avatar
  • 43
2 votes
1 answer
129 views

Relation between multivariate estimation error and differential entropy

On page 255 of the book "Elements of information theory" by Thomas M. Cover and Joy A. Thomas, there is a theorem: For any random variable $X$ and estimator $\hat{X}$, $$E(X-\hat{X})^2 \geq \...
CASIA-LH's user avatar
2 votes
0 answers
264 views

Prove or disprove a mutual information inequality

I have $n$ IID Bernoulli random variables denoted by $X_1,X_2,\ldots X_n$ with parameter $p$. I am interested in knowing if the following inequality involving mutual information holds : $\boxed{\max_{...
wanderer's user avatar
2 votes
1 answer
292 views

Mutual information between two discrete random variables

I have 2 IID random variables $X_1$ and $X_2$ with $Bern(p)$ distribution. I have another binary random variable $Y$ taking values in $\{0,1\}$. I am interested in comparing the following 2 mutual ...
wanderer's user avatar
10 votes
2 answers
547 views

The origin of the natural base in statistical mechanics

In modern treatments of statistical mechanics, the natural base is conventionally used for the Gibbs and Boltzmann entropy without careful justification. While I am aware that the properties of the ...
Aidan Rocke's user avatar
  • 3,871
5 votes
0 answers
191 views

Divergence for Bhattacharya Information matrix

The Fisher information matrix (in the scalar parameter case) can be obtained from the Kullback-Leibler divergence by $$g(\theta) = -\frac{\partial}{\partial \theta}\frac{\partial}{\partial \theta'}D(...
Ashok's user avatar
  • 779
2 votes
1 answer
294 views

An inequality in the optimality of Bayes' theorem

$\DeclareMathOperator\Ent{Ent}\newcommand{\prior}{\mathrm{prior}}\newcommand\Data{\mathrm{Data}}$I came across this paper on the optimality of Bayes' theorem https://sinews.siam.org/Portals/Sinews2/...
Chp's user avatar
  • 23
17 votes
4 answers
2k views

Geometric interpretations of the exponential of entropy

Question: Might there be a natural geometric interpretation of the exponential of entropy in Classical and Quantum Information theory? This question occurred to me recently via a geometric inequality ...
Aidan Rocke's user avatar
  • 3,871
1 vote
0 answers
428 views

When inequality in Mrs. Gerber's lemma is almost equality?

Let $X=x_1\ldots x_n$ be a random variable. Assume that every $x_i$ takes values in $\{0,1\}$. Assume also that for every $I \subseteq \{1,\ldots, n\}$ the Shannon entropy of random value $X_I$ [if $I ...
Alexey Milovanov's user avatar
2 votes
0 answers
132 views

A result of the covering number

Suppose $\mathcal{F} = \{f_x : x \in \mathbb{R}^d \}$ and each $f_x$ shares the same law $P$. If $\mathcal{F}$ is a class of uniformly bounded functions satisfying $L_r$-continuity, i.e. $\forall f \...
香结丁's user avatar
  • 331
0 votes
1 answer
582 views

Integrability of $\int \log(f(x)) f(x) dx$ for a probability density function $f$

I am looking for weak conditions when a probability density function $f$ on $\mathbb{R}^d$ has a finite integral $$ \int_{\mathbb{R}^d} \log(f(x)) f(x) dx. $$ Any references would be appreciated.
Austin's user avatar
  • 3
5 votes
3 answers
533 views

Is there a quantum analog of Kolmogorov Complexity?

Kolmogorov Complexity (interpreted in terms of shortest program computing a string) and Shannon Entropy are quite similar. Since there is a quantum entropy is it reasonable to ask if there is quantum ...
Turbo's user avatar
  • 13.9k
8 votes
1 answer
486 views

The entropy of a partition of unity

A partition of unity can be thought of as a blurred out set partition: identify the fibers of the set partition with their indicator functions; the sum of these indicators is $1$. I would like to ...
Yakov Shklarov's user avatar
0 votes
1 answer
260 views

Entropy of a refinement of a partition

We consider a probability space $(X, B, \mu)$. Let $\alpha$ and $\beta$ be countable partitions of X. We suppose $\beta$ is a refinement of $\alpha$, ie that every set in $\alpha$ is a union of sets ...
catbow's user avatar
  • 41
6 votes
2 answers
502 views

Shannon entropy and doubly stochastic matrices

Suppose that $A$ is a stochastic matrix. We know that if $A$ is doubly stochastic, then $H(Ap)\geq H(p)$ where $H$ is Shannon entropy and $p$ is a probability vector. Is the converse true? i.e., if $H(...
Aram's user avatar
  • 109
3 votes
1 answer
247 views

Trace entropies

I'm studying relationships between trace entropy functionals and combinatorics and I'm faced with the following problem. Lets $\mathcal {D}$ be the following differential operator $1 -x\cdot \cfrac{d}{...
Gianfranco's user avatar
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 ...
Phobos's user avatar
  • 131
2 votes
1 answer
293 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-...
mw19930312's user avatar
0 votes
0 answers
404 views

Is there a difference between using nats and bits to express entropy?

It seems to me like questions involving decimal vs binary representations of some number are not particularly interesting: for instance $\pi$ or $\sqrt{2}$ are conjectured to be normal in every base, ...
Ryan's user avatar
  • 226
1 vote
1 answer
149 views

With only two characters allowed, is it possible to efficiently reference a 256 character alphabet in a string?

Let us use 0 and 1 for the binary parallel. You have 256 characters you need to reference, imagining a 256 character alphabet. You can only use a string to reference them that contains 0 and 1. The ...
Bane Williams's user avatar
11 votes
0 answers
307 views

Entropy, magnitude, diversity of finite metric spaces in number theory

I was reading the article by Tom Leinster, (Maximizing diversity in biology and beyond, arXiv link), and find it very interesting. Since I was searching for entropies of finite metric spaces I found ...
user avatar
0 votes
1 answer
181 views

Bounding information of expression

Cross posted to theory exchange - https://cstheory.stackexchange.com/questions/45610/bounding-information-of-expression Suppose $u_1,\ldots,u_n$ are uniformly iid in $\{0,1\}$. Let $x_1,\ldots,x_n$ ...
Andy's user avatar
  • 515
1 vote
0 answers
83 views

Convexity of conditional relative entropy for Markov distributions

Consider two Markov processes $p$ and $q$. The conditional relative entropy between them is \begin{align} D(p\parallel q)& =\sum_a p(a)\sum_b p(b\mid a)\log\frac{p(b\mid a)}{q(b\mid a)}\\ & =\...
doubleG's user avatar
  • 11
4 votes
1 answer
196 views

Polynomial time decodable binary linear codes achieving $GV$ bound?

Are there explicit or random construction of linear codes that achieve the $GV$ bound with polynomial time decodable property with alphabet size $q=2$? Tsfasman, Manin, Vladut beat the bound at ...
Turbo's user avatar
  • 13.9k
3 votes
2 answers
323 views

Lower bound Renyi divergence between two discrete probability distributions

I am trying to understand the proof of Lemma 1 in this paper (Section 9.2). The proof shows that given a discrete probability distribution $P=(p_1,p_2,...,p_k)$ where $p_1 \geq p_2 \geq ... \geq p_k$,...
Elwood Crandall's user avatar
3 votes
3 answers
392 views

Asymptotic value of the Shannon entropy

I would like to evaluate the asymptotic value of the following sum: $$f(N)=\frac{1}{2^N}\sum_{n=0}^{N} \binom{N}{n} \log_{2} \binom{N}{n}$$ This is related to the computation of the Shannon entropy. ...
Ryan's user avatar
  • 31
23 votes
1 answer
767 views

The Euler-Mascheroni constant and entropy

I would like to know if I have discovered or merely rediscovered the following pretty fact. A partition of $[0,1]$ into intervals of lengths $p_{i, i=1\ldots n}$ induces a probability distribution ...
David Feldman's user avatar
3 votes
4 answers
1k views

Apply doubly stochastic matrix M to a probability vector, then entropy increases?

Consider a vector $p =(p_1,\dots,p_n)$, $p_i>0$, $\sum p_i = 1$ and a matrix $M_{ij}$, which is doubly stochastic: $\sum_i M_{ij} = 1, \sum_j M_{ij} = 1, M_{ij} > 0$. Question 1 Just apply ...
Alexander Chervov's user avatar
2 votes
0 answers
92 views

What are the moments of Kolmogorov Complexity for a Random Variable?

Given a random variable $X$ distributed under some computable distribution $P$ we have, $$0 \le E[K(X)] - H(P) \le K(P)$$ Where $H(P)$ is the entropy of $P$. I tried using Hoeffding concentration ...
Zachary W. Robertson's user avatar
8 votes
1 answer
363 views

Characterization of KL divergence for continuous variables?

This is an analog of an older question: What characterizations of relative information are known? With the modification that I’m interested in the case when the distribution is over something that’s ...
zzz's user avatar
  • 928
18 votes
3 answers
3k views

Entropy and total variation distance

Let $X$, $Y$ be discrete random variables taking values within the same set of $N$ elements. Let the total variation distance $|P-Q|$ (which is half the $L_1$ distance between the distributions of $P$ ...
H A Helfgott's user avatar
  • 20.2k
5 votes
2 answers
848 views

Can the differential entropy of a continuous distribution with lebesgue integrable density be negative infinity?

Define the (differential) entropy for a density $f$ as $$ H(f) :=-\int_{0}^{1} f(x) \log_{2}(f(x)) dx \, .$$ I am trying to find a $f \in L_{1}([0,1])$ such that $f\geq 0, \int_{0}^{1} f(x) dx = 1$...
Tejas Bhojraj's user avatar
4 votes
1 answer
283 views

Is there an integer-valued analogue of information entropy?

Let $H_n : (\langle 0,1 \rangle \cap \mathbb{Q})^n \to \langle 0,\log_2 n \rangle, \; H_n(P) = -\sum_{i=1}^n P_i \log_2 P_i, \; \sum_i P_i = 1$ be the information entropy on rationals. I am looking ...
user1747134's user avatar
4 votes
0 answers
228 views

Maximazing the joint entropy given the probability of equality

Consider 2 independent random variables $X$ and $Y$ with values in $A=\{0, 1, \ldots, q-1\}$. Suppose that $P(X=Y)$ is equal to some constant $\varepsilon$. What is the maximal entropy $H(X, Y)$? At ...
Nikita's user avatar
  • 41
1 vote
0 answers
432 views

What is the maximum entropy distribution over the integers

Let $μ=0,σ>0$. What is the maximum entropy distribution over the integers with mean $μ$ and variance $σ^2$? Is Skellam distribution a maximum entropy distribution? Is there a closed-form ...
Ioannis Papoutsidakis's user avatar
2 votes
0 answers
50 views

Do averaged binary symmetric channels maximize mutual information?

This is a refined version of Do binary symmetric channels maximize mutual information?, which was answered negatively. Let the random variables $(X, Y)$ be a doubly symmetric binary source with ...
Georg Pichler's user avatar