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Related papers: The Birthday Problem and Zero-Error List Codes

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Random access codes are an intriguing class of communication tasks that reveal an operational and quantitative difference between classical and quantum information processing. We formulate a natural generalization of random access codes and…

Quantum Physics · Physics 2022-06-22 Teiko Heinosaari , Leevi Leppäjärvi

In this work we analyze the problem of, given the probability distribution of a population, questioning an unknown individual that is representative of the distribution so that our uncertainty about certain characteristics is significantly…

Computational Complexity · Computer Science 2026-01-22 David Pantoja , Ismael Rodriguez , Fernando Rubio , Clara Segura

Previously referred to as `miraculous' in the scientific literature because of its powerful properties and its wide application as optimal solution to the problem of induction/inference, (approximations to) Algorithmic Probability (AP) and…

Information Theory · Computer Science 2018-04-16 Hector Zenil , Liliana Badillo , Santiago Hernández-Orozco , Francisco Hernández-Quiroz

The likelihood encoder with a random codebook is demonstrated as an effective tool for source coding. Coupled with a soft covering lemma (associated with channel resolvability), likelihood encoders yield simple achievability proofs for…

Information Theory · Computer Science 2013-08-01 Paul Cuff , Eva C. Song

A typical goal of research in combinatorial optimization is to come up with fast algorithms that find optimal solutions to a computational problem. The process that takes a real-world problem and extracts a clean mathematical abstraction of…

Data Structures and Algorithms · Computer Science 2025-07-22 Sheikh Shakil Akhtar , Jayakrishnan Madathil , Pranabendu Misra , Geevarghese Philip

A long-running difficulty with conventional game theory has been how to modify it to accommodate the bounded rationality of all real-world players. A recurring issue in statistical physics is how best to approximate joint probability…

Statistical Mechanics · Physics 2007-05-23 David H. Wolpert

Shannon's channel coding theorem characterizes the maximal rate of information that can be reliably transmitted over a communication channel when optimal encoding and decoding strategies are used. In many scenarios, however, practical…

Information Theory · Computer Science 2023-07-06 Jonathan Scarlett , Albert Guillén i Fàbregas , Anelia Somekh-Baruch , Alfonso Martinez

A collaborative distributed binary decision problem is considered. Two statisticians are required to declare the correct probability measure of two jointly distributed memoryless process, denoted by $X^n=(X_1,\dots,X_n)$ and…

Information Theory · Computer Science 2016-04-11 Gil Katz , Pablo Piantanida , Merouane Debbah

Ultrafast physical random bit generation at hundreds of Gb/s rates, with verified randomness, is a crucial ingredient in secure communication and have recently emerged using optics based physical systems. Here we examine the inverse problem…

Signal Processing · Electrical Eng. & Systems 2019-11-05 Shira Sardi , Herut Uzan , Shiri Otmazgin , Yaara Aviad , Michael Rosenbluh , Ido Kanter

We introduce and examine the {\em Holiday Gathering Problem} which models the difficulty that couples have when trying to decide with which parents should they spend the holiday. Our goal is to schedule the family gatherings so that the…

Data Structures and Algorithms · Computer Science 2014-08-12 Amihood Amir , Oren Kapah , Tsvi Kopelowitz , Moni Naor , Ely Porat

One can often encounter claims that classical (Kolmogorovian) probability theory cannot handle, or even is contradicted by, certain empirical findings or substantive theories. This note joins several previous attempts to explain that these…

Probability · Mathematics 2019-01-24 Ehtibar N. Dzhafarov , Maria Kon

Probabilistic models are proposed for bounding the forward error in the numerically computed inner product (dot product, scalar product) between of two real $n$-vectors. We derive probabilistic perturbation bounds, as well as probabilistic…

Numerical Analysis · Mathematics 2019-06-26 Ilse C. F. Ipsen , Hua Zhou

We consider communication over memoryless channels using low-density parity-check code ensembles above the iterative (belief propagation) threshold. What is the computational complexity of decoding (i.e., of reconstructing all the typical…

Information Theory · Computer Science 2007-07-13 Cyril Measson , Andrea Montanari , Tom Richardson , Rudiger Urbanke

An additive noise channel is considered, in which the distribution of the noise is nonparametric and unknown. The problem of learning encoders and decoders based on noise samples is considered. For uncoded communication systems, the problem…

Information Theory · Computer Science 2021-11-17 Nir Weinberger

We study the problem of efficient compression of a stochastic source of probability distributions. It can be viewed as a generalization of Shannon's source coding problem. It has relation to the theory of common randomness, as well as to…

Quantum Physics · Physics 2016-09-08 Andreas Winter

The coordination of autonomous agents is a critical issue for decentralized communication networks. Instead of transmitting information, the agents interact in a coordinated manner in order to optimize a general objective function. A target…

Information Theory · Computer Science 2016-11-15 Maël Le Treust

Let $S$ be a finite set, and $X_1,\ldots,X_n$ an i.i.d. uniform sample from $S$. To estimate the size $|S|$, without further structure, one can wait for repeats and use the birthday problem. This requires a sample size of the order…

Statistics Theory · Mathematics 2026-04-28 Sourav Chatterjee , Persi Diaconis , Susan Holmes

We study the problem of communicating over a discrete memoryless two-way channel using non-adaptive schemes, under a zero probability of error criterion. We derive single-letter inner and outer bounds for the zero-error capacity region,…

Information Theory · Computer Science 2021-09-13 Yujie Gu , Ofer Shayevitz

The Bayesian brain hypothesis has been a leading theory in understanding perceptual decision-making under uncertainty. While extensive psychophysical evidence supports the notion of the brain performing Bayesian computations, how…

Neurons and Cognition · Quantitative Biology 2026-03-05 Po-Chen Kuo , Edgar Y. Walker

Information theory provides tools to predict the performance of a learning algorithm on a given dataset. For instance, the accuracy of learning an unknown parameter can be upper bounded by reducing the learning task to hypothesis testing…

Quantum Physics · Physics 2026-04-21 Evan Peters
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