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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
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
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
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
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
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
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
1 answer
306 views

About Renyi entropy

If one is given a joint probability distribution over a finite set of discrete random variables then I guess there a notion of $\alpha-$Renyi entropy defined for it as $S_\alpha (X_1,..,X_n) = \frac{...
gradstudent's user avatar
  • 2,246
1 vote
1 answer
304 views

Entropy on a draw from a random distribution.

Suppose I am attempting to calculate the entropy of a continuous, normally distributed random variable $X$, from the distribution $\mathcal{N}(\mu, \sigma)$. This is easy to to do - I just calculate $...
Danny W.'s user avatar
  • 229
5 votes
1 answer
778 views

Calculate channel capacity of general channel under constraint

Given a conditional distribution $P_{Y\mid X}$ I'd like to find the prior distribution $P_X$ that maximizes the mutual information $I(X;Y)$ with $P_Y(y)=\int P_{Y\mid X}(y\mid x)P_X(x) \, \text{d}x$ (...
user31757's user avatar
9 votes
2 answers
462 views

Entropy conjecture for distributions over $\mathbb{Z}_n$

Suppose we have two independent random variables $X$ (with distribution $p_X$) and $Y$ (with distribution $p_Y$) which take values in the cyclic group $\mathbb{Z}_n$. Let $Z = X +Y$, where the ...
VSJ's user avatar
  • 1,034
1 vote
4 answers
3k views

Differential Entropy of Random Signal

Prove that the Normal (Gaussian) Distribution with a given Variance $ {\sigma}^{2} $ maximizes the Differential Entropy among all distributions with defined and finite 1st Moment and Variance which ...
Royi's user avatar
  • 115