Questions tagged [it.information-theory]
Questions in Information Theory
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What are the two quantities involved in the tradeoff for a language to follow Zipf's law?
In any human (and non-human) language the frequency distribution of words follows Zipf's law, which states that the slope of the linear regression for the frequency distribution of words vs the rank ...
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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 ...
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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 $n$ ...
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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....
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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 ...
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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 ...
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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 ...
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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 $...
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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 ...
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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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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 ...
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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=...
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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 ...
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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. ...
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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 ...
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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 ...
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"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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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,...
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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 ...
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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
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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 ...
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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,...
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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 ...
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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:\...
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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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Data processing inequality for interaction information
The interaction information is defined as $I(X;Y)-I(X;Y|Z)$. Let $Z-(X, Y) -(X', Y')$ be a Markov chain. Is there an inequality similar to the data processing inequality, relating $I(X';Y')-I(X';Y'|Z)...
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Why Asymptotic Equipartition Property theorem proofs assume the source is memoryless?
I do not understand the assumption $X_1, X_2, \cdots$ are i.i.d. ~p(x) in the AEP proofs I have seen. I have read some different sources for understanding the Asymptotic Equipartition Property. Using ...
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Kolmogorov Complexity of a Decidable Language
The Kolmogorov Complexity (KC) of a string $y$ is the size of the smallest program $f$ and input $x$ that: $y = f(x)$. Let's define a variation of Kolmogorov's complexity$^1$. Suppose a decidable ...
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Notation in proof for Asymptotic Equipartition Property
In the following lecture notes chapter 3, page 12-13, they state the following
We begin by introducting some important notation:
- For a set $\mathcal{S},|\mathcal{S}|$ denotes its cardinality (...
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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 $\...
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Notation of sequences in rate distortion theory
I have been reading whatever sources I could get my hands on today, regarding this problem.
Most notes online about rate distortion theory come from the book Elements of Information Theory by Thomas ...
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Expected vs worst-case communication complexity
In the set disjointness problem of 2-party communication complexity, Alice and Bob are both given an $n$-bit string as input; denoted by $X$ for Alice's input, and $Y$ for Bob's input. They need to ...
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Strong data-processing inequality: bound $TV(T_{\#}P_0,T_{\#}P_1)$ if $\|T(x)-x\|_\infty \le \varepsilon;\forall x \in \mathbb R^p$
Disclaimer. I've moved this question from MO hoping that here is the right venue. Also, this is my first post on this channel, so please have some patience.
So, Iet $X = (X,d)$ be a Polish space, ...
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Representing data with Shannon entropy predicted bits
Let us assume a file based on a character set where each character has equal probability of occurance. This will result in the maximum entropy for that character set. On calculating the entropy, let ...
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Maximization of Mutual Information
Let $X\in\{0,1\}^d$ be a Boolean vector and $Y, Z\in\{0,1\}$ are Boolean variables. Assume that there is a joint distribution $\mathcal{D}$ over $Y, Z$ and we'd like to find a joint distribution $\...
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Minimum number of hours of speech needed to train a neural net to recognize speech [closed]
From a theoretical computer science point of view, is there a lower limit on the number of hours of speech needed to train a neural net to translate speech to text? An estimate from CMU is 3000-5000 ...
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Chain rule for KL divergence
Is there an inequality to relate the KL divergence of two joint distribution and the sum of the KL divergence of their marginals? Or in particular, is there a proof or a counter example for the ...
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Why not include private randomness in internal communication information definition?
I am using https://www.cs.toronto.edu/~toni/Courses/CommComplexity2014/Lectures/lecture12.pdf as a reference.
This isn't exactly a research question but I can't find a good place to ask it.
Suppose ...
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Expected vs actual amount of information leaked by an $l$-bits message
Say we have a random variable $X$ that contains $k$ bits of information, and a message $M = f(X)$ ($M$ is deterministic given $X$) that is $l$ bits long, where $l<k$. This implies $H(X) = k$ and $...
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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 $\mathcal{Y}$....
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Is a binary sequence computable iff the Kolmogorov complexity of its initial segments is bounded?
Disclaimer: I am mostly unfamiliar with theoretical computer science, making it hard for me to navigate literature in the field. I ask the following out of curiosity.
Background/Motivation: Coming ...
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Minimal information needed for determine some function
From calculus, we know that if someone has a continuous function $f$, it is enough to know $f$'s values on the rationals in order to know $f$ on the entire line. In some sense, a "countable amount of ...
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Is algorithmic information theory still evolving?
I am currently looking for a subject for a thesis and encountered the field of algorithmic information theory.
The field seems very interesting for me, but it seems everything is the field was done ...
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