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Questions tagged [it.information-theory]

Questions in Information Theory

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36 views

Channel Capacity & Dependency Graph

In a communication channel, $\{ X_i \}_{i=1}^n$ are inputs and $\{ Y_i \}_{i=1}^n$ are the corresponding outputs. We represent the dependency relations by a graph with $2n$ nodes (one for each $X_i$ ...
0 votes
1 answer
37 views

Feature selection problem under promise

Are there well used examples of feature selection problem where the problem is defined under certain promise? Let's say the task is to select the minimum number of features such that the mutual ...
1 vote
0 answers
40 views

Practical Applications of Information Algebras

I've started reading Information Algebras, Kohlas (the Wikipedia may give you the gist) and I am curious as to whether any ideas from this theory/book could be practically implemented, perhaps as some ...
1 vote
1 answer
78 views

Detecting Erroneous Corrections

A block code $C$, with minimum distance $d$ can be used to: Detect $d - 1$ errors Correct $\lfloor\frac{d - 1}{2}\rfloor$ errors However, the above usually assumes that the number of errors that are ...
0 votes
0 answers
24 views

Is it accurate to describe a computer as a dynamic memory state?

is this an accurate statement? And where can I find out more about these topics? At any point in time a computer is holding a memory state. Because the computer is moving in various ways we can call ...
1 vote
1 answer
122 views

Relation Between Different Definitions of Information Distance

I'm reading the fourth edition of An Introduction to Kolmogorov Complexity and Its Applications by Li and Vitanyi. In Section 8.3 of the book, it introduces the concept of "information distance.&...
0 votes
1 answer
100 views

Maximum theoretical compression ratio for real-valued data

Given a sequence of $N$ real-valued vectors $\mathbf{v_1}, \mathbf{v_2}, ..., \mathbf{v_N}$, each of dimension $d$, do any of the below bounds exist? The minimum number of real-valued vectors of ...
1 vote
0 answers
41 views

Why the measure of information complexities for passive and active learning are increasing in research communities?

I am a PhD student working on the theory of active learning. Over the years, accepted papers in COLT and ALT for active learning are focused on approaches that almost all of them define new ...
1 vote
1 answer
121 views

Information Bottleneck - Calculating the Mutual information between the Labels and the Features [closed]

I am trying to understand the Nonlinear Information Bottlecneck paper along with their implementation, but I am confused as to what is actually being calculated in the Mutual information $(I(Y, M))$ ...
0 votes
0 answers
57 views

Does Co-occurrence Information Differ Qualitatively From Shannon and Algorithmic Information?

In Distributed Computation as Hierarchy Michael Manthey argues that co-occurrence of indistinguishables (critical for quantum theory) supplies spatial information that qualitatively differs from both ...
17 votes
6 answers
23k views

Which is the limit of lossless compression data? (if there exists such a limit)

Lately I've been dealing with compression-related algorithms, and I was wondering which is the best compression ratio that can be achievable by lossless data compression. So far, the only source I ...
61 votes
14 answers
4k views

Information Theory used to prove neat combinatorial statements?

What's your favorite examples where information theory is used to prove a neat combinatorial statement in a simple way ? Some examples I can think of are related to lower bounds for locally decodable ...
2 votes
1 answer
990 views

Can the mutual information of a "cell" be negative?

Please forgive me if this is not the right Stack Exchange (I also posted it at Cross Validated). Please also forgive me for inventing terms. For discrete random variables X and Y, the mutual ...
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0 answers
51 views

Can information, eg. Shannon Entropy, be considered an absolute value?

This question is a distillation of my question here: How do I calculate the information content of a mass spectrum? Using a theoretical instrument that makes perfect measurements of fundamental ...
1 vote
2 answers
218 views

How much information does it take to specify, not each member of a group, but any one member?

It takes exactly $\log_2 n := \lg n$ bits of information to specify a number from $\{1,2,\ldots,n\}.$ Likewise, it takes $\lg{n\choose s}$ bits of information to specify a subset of $s$ out of the $n$ ...
0 votes
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65 views

How do I calculate the information content of a mass spectrum?

Ions in a mass spectrum are represented using two independent values for the mass-to-charge ratio [m/z] of the ion and it's relative abundance. Here's an example for caffeine from HMDB: https://hmdb....
0 votes
1 answer
49 views

Looking for information on Information Theory applied to image pixelation

I'm in seventh grade and am doing a science project about how age and gender affects people's ability to recognize pixelated images. For background research I have been reading about information ...
3 votes
0 answers
23 views

Modelling channels without specifying input alphabets

The standard mathematical model of a communication channel is that of a stochastic matrix $(C(x|a))_{a \in A, x \in X}$, where $A$ is the input alphabet and $X$ the output alphabet. This definition ...
1 vote
1 answer
214 views

Uniqueness of the distribution maximizing the channel capacity

Setting: We look at a discrete memoryless channel which takes an input probability distribution acting over symbols in $\mathcal{X}$ to an output probability distribution over symbols in $\mathcal{Y}$....
1 vote
0 answers
92 views

Generalizing Fano's inequality

Fano's inequality says the following: Theorem: Let $X$ be a random variable with range $M$. Let $\hat{X} = g(Y)$ be the predicted value of $X$ given some transmitted value $Y$, where $g$ is a ...
2 votes
0 answers
182 views

On the number of optimal prefix-free binary codes [closed]

Let $T$ be a text of length $L$ containing the symbols $$\mathcal{A}=\{a_1, a_2, \ldots, a_n\},$$ where each symbol appears at least once and no other symbol appears in $T$. Define the weights $$\...
0 votes
1 answer
189 views

Information theoretic arguments for complexity

This Wikipedia article,Decision tree model, states that decision tree complexity lower bound $O(n \log_2 n)$ for sorting problem is information theoretic since any algorithm ( modeled as decision ...
0 votes
0 answers
60 views

Is there a name/terminology for binary codes with evenly spaced number of ones?

I am generating a random binary matrix $A \in \{0, 1\}^{m \times n}$ with the number of ones in each row set to evenly spaced numbers from an interval. For example, if $n=50$, the number of ones for $...
2 votes
0 answers
71 views

Origin of Berge's (Weak) Perfect Graph Conjecture

In an account of his thought process (refer p. 3) leading up to the perfect graph conjecture (which I'm preparing a seminar talk on), C. Berge states what seems to be a crucial step: (1) a graph $G$ ...
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0 answers
62 views

Interesting statistical experiment concerning data compression

I want to present the following statistical experiment concerning data compression, on which I will ask you to predict the result obviously justifying the choice made. The statistical experiment is ...
3 votes
1 answer
172 views

Maximal uniquely decodable codes

This question is about the Kraft-McMillan inequality: If $w_1,\ldots,w_n$ are words of lengths $l_1,\ldots,l_n$ from an alphabet with $r$ letters, which form a uniquely decodable code, then $$ \sum_{i=...
0 votes
1 answer
68 views

meaning of "algorithms that do not resample points" in the algorithms that do not resample points theorem

The No Free Lunch theorems for search and optimization demonstrate that for search/optimization problems in a limited search space, where the points being searched through are not resampled, the ...
1 vote
1 answer
173 views

Can theoretical computer science be combined with mechanism and information design and applications in financial markets

I am considering to take a position as a phd student in a computer science department. I am a mathematician with a master degree in finance and my research interests are mainly focused in game theory. ...
4 votes
0 answers
260 views

Maximize the mutual information between 2 discrete random variables

I have two random variables $X$ and $Y$. $X$ follows Poisson-Binomial distribution with parameters $\{q_1, \ldots, q_k\}$. Thus, $X$ can take values in the set $\{0,1,\ldots,k\}$. $Y$ is a binary ...
2 votes
0 answers
88 views

Approximate (in hamming distance) subset representation

Let us have a set $S$ and a subset $T \subseteq S$. I want to find an approximate representation of $T$, i.e. I want to represent (exactly) a set $T'$ that is close to $T$. That is, I want the ...
9 votes
6 answers
2k views

Where does the information in a fractal come from?

When I view a fractal such as the Mandelbrot, my first thought is, where did this interesting picture come from. For a picture of this complexity, the information that generated this picture must be ...
9 votes
0 answers
160 views

"Looking for help understanding a proof by Gossner (1998)."

Although there is no use of cryptographic protocols in Gossner (1998), the author refers to protocols of communication and he has a main result that I struggle to prove, because he does not use a ...
1 vote
0 answers
113 views

Does any physical process constitute a "computation"? [closed]

I am trying to sharpen the convex hull of what seems like a (surprisingly) stubborn concept to enclose based on answers here, as well as conversations with others, around the nature of what actually ...
5 votes
1 answer
241 views

Upper bound on the expected number of correct bits via a "lossy compression"

Consider the following "compression problem" for a pair $(C,D)$ of algorithms: $C$ receives a uniformly random $x \in \{0,1\}^n$ and outputs a smaller bit string $y \in \{0,1\}^s$. Algorithm ...
3 votes
2 answers
358 views

Information and Coding Theory Texts

I am coming from a pure mathematics (in analysis) background and am curious to learn some information and coding theory. I am after some recommendations on texts. Due to my personal background I am ...
4 votes
1 answer
208 views

Does this notion of entropy have a name?

Recently I stumbled upon the following notion of entropy which seems quite natural to me. I am looking for its "real" name and/or any references where it might come up. I tried searching ...
32 votes
5 answers
3k views

Efficiently computable variants of Kolmogorov complexity

Kolmogorov prefix complexity (i.e. $K(x)$ is the size of minimal self-delimiting program that outputs $x$) has several nice features: It corresponds to an intuition of giving strings with patters or ...
1 vote
0 answers
56 views

sophistication or logical depth to detect intelligent extra-terrestrial species

From my understanding, Algorithmic information theory (AIT) gives some ways to define the amount of « structure » in a string: for example sophistication or logical depth (see for instance [1]), can ...
1 vote
0 answers
127 views

Deterministic one way communication complexity for message with arbitrary length

Let Alice have a binary string of length $n$ that it wants to send to Bob along a one-bit communication channel. However, Bob does not know the length of the message. I have been looking into ...
0 votes
0 answers
173 views

Error in entropy properties in Mathematical Theory of Cryptography by Claude E. Shannon

I am reading this classic paper by Claude E. Shannon and I think there may be a couple of errors in his description of the properties of Entropy/Uncertainty. The screenshot shown at the bottom of this ...
10 votes
1 answer
446 views

Is subtractive dithering the optimal algorithm for sending a real number using one bit?

Consider the problem of sending a real number $x\in[0,1]$ using a single bit $X\in\{0,1\}$ in an unbiased manner. We assume that the sender and receiver have access to shared randomness $h\sim U[-1/2,...
3 votes
3 answers
5k views

Difference between self-information and entropy

I get a bit confused about different definitions of entropy and/or self-information. Entropy? $$ H(X) = - \sum_{x \in X} P_X(x) \cdot \log{\left(P_X(x)\right)} $$ Self-information? $$ I(x) = - \...
0 votes
1 answer
154 views

Volume of elements mapped to the same codeword is $2^{H(X|\hat{X})}$

In this paper by Tishby, Pereira and Bialek they mention on page 4 in the Relevant quantization chapter the setting is the following; Given some signal space $X \sim p(x)$ and a quantized codebook $\...
0 votes
1 answer
118 views

Why isn’t information-probability relationship linear? [closed]

I am completely new to information theory. I was learning about information content but couldn’t make sense of why the relationship between information content and probability isn’t linear? And why it ...
3 votes
1 answer
226 views

Converting a Bernoulli to a Gaussian

It is not hard to see that, given one sample from a univariate unit-variance Gaussian $X\sim \mathcal{N}(\mu,1)$ with unknown $\mu$ s.t. $0<|\mu|\leq 1$, one can simulate one draw from a "...
0 votes
0 answers
15 views

Capacity of spike-based neuronal code

Assume that a neuronal population $A$ is connected to a neuronal population $B$ by a bunch of synapses - one-directional channels that propagate spikes. For simplicity assume that the current ...
4 votes
1 answer
201 views

Generating $k$ random bits from a pdf with entropy $H(p) = k$

All the sources online say that, intuitively, a distribution with entropy $k$ has $k$ bits of pure randomness in it. So can we formalize this as follows? Suppose I can only sample from my distribution,...
1 vote
0 answers
85 views

Difference between a lossy encoder and a noisy channel in Information Theory

$S \to X \to Y \to \hat{S}$ $\text{source} \to \text{input} \to \text{output} \to \text{target}$ In information theory introductory books, an encoder is usually defined as a deterministic function $f:\...
2 votes
0 answers
199 views

Damerau–Levenshtein distance with transposition of non-adjacent characters?

Wondering if it's possible to calculate Damerau–Levenshtein distance with transposition of non-adjacent characters (DL distance allows transposition of immediately adjacent characters only). I want ...
2 votes
1 answer
207 views

Explicit Bits-back Coding (a.k.a. Free Energy Coding) applied to Gaussian mixtures

I've been trying to understand Bits-back coding (Frey, B. J., and G. E. Hinton. 1997.) a bit more (pun intended), which can be used to encode data with latent variable models. This tutorial by Pieter ...

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