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This paper illustrates the richness of the concept of regular sets of time bounds and demonstrates its application to problems of computational complexity. There is a universe of bounds whose regular subsets allow to represent several time…

Computational Complexity · Computer Science 2013-09-24 Armin Hemmerling

Solomonoff's central result on induction is that the posterior of a universal semimeasure M converges rapidly and with probability 1 to the true sequence generating posterior mu, if the latter is computable. Hence, M is eligible as a…

Machine Learning · Computer Science 2007-07-16 Marcus Hutter , Andrej Muchnik

In 1957, Lacombe initiated a systematic study of the different possible notions of "computable topological spaces". However, he interrupted this line of research, settling for the idea that "computably open sets should be computable unions…

Logic · Mathematics 2024-11-25 Emmanuel Rauzy

In this paper we study the adaptivity of submodular maximization. Adaptivity quantifies the number of sequential rounds that an algorithm makes when function evaluations can be executed in parallel. Adaptivity is a fundamental concept that…

Data Structures and Algorithms · Computer Science 2018-04-18 Eric Balkanski , Aviad Rubinstein , Yaron Singer

In "Reliable Communication in the Absence of a Common Clock" (Yeung et al., 2009), the authors introduce general run-length sets, which form a class of constrained systems that permit run-lengths from a countably infinite set. For a…

Information Theory · Computer Science 2010-01-14 Georg Böcherer , Rudolf Mathar , Valdemar Cardoso da Rocha Junior , Cecilio Pimentel

Bayesian computation for filtering and forecasting analysis is developed for a broad class of dynamic models. The ability to scale-up such analyses in non-Gaussian, nonlinear multivariate time series models is advanced through the…

Methodology · Statistics 2022-06-07 Isaac Lavine , Andrew Cron , Mike West

Evaluating the performance of generative models in image synthesis is a challenging task. Although the Fr\'echet Inception Distance is a widely accepted evaluation metric, it integrates different aspects (e.g., fidelity and diversity) of…

Computer Vision and Pattern Recognition · Computer Science 2021-06-07 Ryoungwoo Jang , Minjee Kim , Da-in Eun , Kyungjin Cho , Jiyeon Seo , Namkug Kim

In this work, we study Bayesian quantum parameter estimation given a finite number of uses of the process encoding one or more unknown physical quantities. For multiple uses, it is conventional to classify quantum metrological protocols as…

Quantum Physics · Physics 2026-02-11 Erik L. André , Jessica Bavaresco , Mohammad Mehboudi

It is not obvious what fraction of all the potential information residing in the molecules and structures of living systems is significant or meaningful to the system. Sets of random sequences or identically repeated sequences, for example,…

Information Theory · Computer Science 2008-01-28 David J. Galas , Matti Nykter , Gregory W. Carter , Nathan D. Price , Ilya Shmulevich

Quantum computation is frequently mischaracterized as the simultaneous execution of exponentially many classical computations. This article offers a conceptual clarification of why this ``branchwise parallelism'' picture is misleading,…

Quantum Physics · Physics 2026-05-20 Karl Svozil

Complex computer codes are often too time expensive to be directly used to perform uncertainty propagation studies, global sensitivity analysis or to solve optimization problems. A well known and widely used method to circumvent this…

Applications · Statistics 2008-04-06 Amandine Marrel , Bertrand Iooss , Francois Van Dorpe , Elena Volkova

The seminal work of Bencz\'ur and Karger demonstrated cut sparsifiers of near-linear size. Subsequent extensions have yielded sparsifiers for hypergraph cuts and more recently linear codes over Abelian groups. A decade ago, Kogan and…

Data Structures and Algorithms · Computer Science 2026-05-19 Joshua Brakensiek , Venkatesan Guruswami

Sequential probability assignment and universal compression go hand in hand. We propose sequential probability assignment for non-binary (and large alphabet) sequences with empirical distributions whose parameters are known to be bounded…

Information Theory · Computer Science 2021-02-09 Michael Drmota , Gil Shamir , Wojciech Szpankowski

We consider coding schemes for computationally bounded channels, which can introduce an arbitrary set of errors as long as (a) the fraction of errors is bounded with high probability by a parameter $p$ and (b) the process which adds the…

Information Theory · Computer Science 2013-03-01 Venkatesan Guruswami , Adam Smith

We study Martin-L\"{o}f random (ML-random) points on computable probability measures on sample and parameter spaces (Bayes models). We consider variants of conditional randomness defined by ML-randomness on Bayes models and those of…

Information Theory · Computer Science 2023-04-24 Hayato Takahashi

Many large scale problems in computational fluid dynamics such as uncertainty quantification, Bayesian inversion, data assimilation and PDE constrained optimization are considered very challenging computationally as they require a large…

Computational Physics · Physics 2020-04-22 Kjetil O. Lye , Siddhartha Mishra , Deep Ray

There are several forms of irreducibility in computing systems, ranging from undecidability to intractability to nonlinearity. This paper is an exploration of the conceptual issues that have arisen in the course of investigating speed-up…

Computational Complexity · Computer Science 2011-06-24 Hector Zenil , Fernando Soler-Toscano , Joost J. Joosten

Approximation of the optimal two-part MDL code for given data, through successive monotonically length-decreasing two-part MDL codes, has the following properties: (i) computation of each step may take arbitrarily long; (ii) we may not know…

Machine Learning · Computer Science 2008-09-15 Pieter Adriaans , Paul Vitanyi

A superredundant clause is a clause that is redundant in the resolution closure of a formula. The converse concept of superirredundancy ensures membership of the clause in all minimal CNF formulae that are equivalent to the given one. This…

Computational Complexity · Computer Science 2022-05-03 Paolo Liberatore

Probabilistic programming languages aim to describe and automate Bayesian modeling and inference. Modern languages support programmable inference, which allows users to customize inference algorithms by incorporating guide programs to…

Programming Languages · Computer Science 2021-04-09 Di Wang , Jan Hoffmann , Thomas Reps
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