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We study the problem of restricting a Markov equivalence class of maximal ancestral graphs (MAGs) to only those MAGs that contain certain edge marks, which we refer to as expert or orientation knowledge. Such a restriction of the Markov…

Machine Learning · Statistics 2025-09-26 Aparajithan Venkateswaran , Emilija Perković

Infinite random sequences of letters can be viewed as stochastic chains or as strings produced by a source, in the sense of information theory. The relationship between Variable Length Markov Chains (VLMC) and probabilistic dynamical…

Probability · Mathematics 2010-07-20 Peggy Cénac , Brigitte Chauvin , Frédéric Paccaut , Nicolas Pouyanne

An important question for a probabilistic program is whether the probability mass of all its diverging runs is zero, that is that it terminates "almost surely". Proving that can be hard, and this paper presents a new method for doing so; it…

Programming Languages · Computer Science 2017-12-27 Annabelle McIver , Carroll Morgan , Benjamin Lucien Kaminski , Joost-Pieter Katoen

We establish an abstract, effective, exponential large deviations type estimate for Markov systems satisfying a weaker form of mixing. We employ this result to derive such estimates, as well as a central limit theorem, for the skew product…

Dynamical Systems · Mathematics 2025-07-17 Ao Cai , Pedro Duarte , Silvius Klein

Metric coinduction is a form of coinduction that can be used to establish properties of objects constructed as a limit of finite approximations. One can prove a coinduction step showing that some property is preserved by one step of the…

Logic in Computer Science · Computer Science 2015-07-01 Dexter Kozen , Nicholas Ruozzi

As it is known, universal codes, which estimate the entropy rate consistently, exist for stationary ergodic sources over finite alphabets but not over countably infinite ones. We generalize universal coding as the problem of universal…

Information Theory · Computer Science 2023-08-01 Łukasz Dębowski

Term Coding asks: given a finite system of term identities $\Gamma$ in $v$ variables, how large can its solution set be on an $n$--element alphabet, when we are free to choose the interpretations of the function symbols? This turns familiar…

Information Theory · Computer Science 2026-01-26 Søren Riis

This paper deals with a universal coding problem for a certain kind of multiterminal source coding network called a generalized complementary delivery network. In this network, messages from multiple correlated sources are jointly encoded,…

Information Theory · Computer Science 2009-04-02 Akisato Kimura , Tomohiko Uyematsu , Shigeaki Kuzuoka , Shun Watanabe

Using terminologies of information geometry, we derive upper and lower bounds of the tail probability of the sample mean. Employing these bounds, we obtain upper and lower bounds of the minimum error probability of the 2nd kind of error…

Statistics Theory · Mathematics 2024-09-10 Shun Watanabe , Masahito Hayashi

We extend the concept of the law of a finite graph to graphings, which are, in general, infinite graphs whose vertices are equipped with the structure of a probability space. By doing this, we obtain a vast array of new unimodular measures.…

Combinatorics · Mathematics 2012-03-13 Igor Artemenko

Coinduction refers to both a technique for the definition of infinite streams, so-called codata, and a technique for proving the equality of coinductively specified codata. This article first reviews coinduction in declarative programming.…

Programming Languages · Computer Science 2020-07-23 François Bry

Markov chain Monte Carlo is a class of algorithms for drawing Markovian samples from high-dimensional target densities to approximate the numerical integration associated with computing statistical expectation, especially in Bayesian…

Computation · Statistics 2018-03-28 Khoa T. Tran

We derive novel upper and lower finite-length bounds of the error probability in joint source-channel coding when the source obeys an ergodic Markov process and the channel is a Markovian additive channel or a Markovian conditional additive…

Information Theory · Computer Science 2017-05-03 Ryo Yaguchi , Masahito Hayashi

Markov chain Monte Carlo (MCMC) algorithms are used to estimate features of interest of a distribution. The Monte Carlo error in estimation has an asymptotic normal distribution whose multivariate nature has so far been ignored in the MCMC…

Statistics Theory · Mathematics 2016-07-05 Dootika Vats , James M. Flegal , Galin L. Jones

We study the problem of combining the outcomes of several different classifiers in a way that provides a coherent inference that satisfies some constraints. In particular, we develop two general approaches for an important…

Machine Learning · Computer Science 2007-05-23 Vasin Punyakanok , Dan Roth

We answer the question which conjunctive queries are uniquely characterized by polynomially many positive and negative examples, and how to construct such examples efficiently. As a consequence, we obtain a new efficient exact learning…

Logic in Computer Science · Computer Science 2022-08-25 Balder ten Cate , Victor Dalmau

In 1977, Keane and Smorodinsky showed that there exists a finitary homomorphism from any finite-alphabet Bernoulli process to any other finite-alphabet Bernoulli process of strictly lower entropy. In 1996, Serafin proved the existence of a…

Probability · Mathematics 2007-05-23 Nate Harvey , Alexander E. Holroyd , Yuval Peres , Dan Romik

Complex reasoning problems are most clearly and easily specified using logical rules, but require recursive rules with aggregation such as count and sum for practical applications. Unfortunately, the meaning of such rules has been a…

Databases · Computer Science 2023-08-29 Yanhong A. Liu , Scott D. Stoller

Matching logic is a logical framework for specifying and reasoning about programs using pattern matching semantics. A pattern is made up of a number of structural components and constraints. Structural components are syntactically matched,…

Logic in Computer Science · Computer Science 2024-11-01 Ádám Kurucz , Péter Bereczky , Dániel Horpácsi

The paper presents exponentially-strong converses for source-coding, channel coding, and hypothesis testing problems. More specifically, it presents alternative proofs for the well-known exponentially-strong converse bounds for almost…

Information Theory · Computer Science 2023-01-18 Mustapha Hamad , Michele Wigger , Mireille Sarkiss