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We introduce the class of constant probability (CP) programs and show that classical results from probability theory directly yield a simple decision procedure for (positive) almost sure termination of programs in this class. Moreover,…

Logic in Computer Science · Computer Science 2019-09-19 Jürgen Giesl , Peter Giesl , Marcel Hark

In this paper, we develop a novel verification technique to reason about programs featuring concurrency, pointers and randomization. While the integration of concurrency and pointers is well studied, little is known about the combination of…

Logic in Computer Science · Computer Science 2024-10-01 Ira Fesefeldt , Joost-Pieter Katoen , Thomas Noll

This paper presents a methodology for temporal logic verification of discrete-time stochastic systems. Our goal is to find a lower bound on the probability that a complex temporal property is satisfied by finite traces of the system.…

Systems and Control · Computer Science 2019-11-22 Pushpak Jagtap , Sadegh Soudjani , Majid Zamani

Lower bounds for some explicit decision problems over the complex numbers are given.

Numerical Analysis · Mathematics 2025-10-20 Gregorio Malajovich

Hypothesis tests and confidence intervals are ubiquitous in empirical research, yet their connection to subsequent decision-making is often unclear. We develop a theory of certified decisions that pairs recommended decisions with…

Econometrics · Economics 2025-02-26 Isaiah Andrews , Jiafeng Chen

Recent successes of game-theoretic formulations in ML have caused a resurgence of research interest in differentiable games. Overwhelmingly, that research focuses on methods and upper bounds on their speed of convergence. In this work, we…

Machine Learning · Computer Science 2020-09-16 Adam Ibrahim , Waïss Azizian , Gauthier Gidel , Ioannis Mitliagkas

While there are many approaches for automatically proving termination of term rewrite systems, up to now there exist only few techniques to disprove their termination automatically. Almost all of these techniques try to find loops, where…

Logic in Computer Science · Computer Science 2010-12-30 René Thiemann , Christian Sternagel , Jürgen Giesl , Peter Schneider-Kamp

A linear constraint loop is specified by a system of linear inequalities that define the relation between the values of the program variables before and after a single execution of the loop body. In this paper we consider the problem of…

Logic in Computer Science · Computer Science 2024-05-24 Quentin Guilmant , Engel Lefaucheux , Joël Ouaknine , James Worrell

The goal of this work is to prove a new sure upper bound in a setting that can be thought of as a simplified function field analogue. This result is comparable to a recent result of the author concerning almost sure upper bound of random…

Number Theory · Mathematics 2025-06-18 Rachid Caich

A formulation of "Ne\v{c}iporuk's lower bound method" slightly more inclusive than the usual complexity-measure-specific formulation is presented. Using this general formulation, limitations to lower bounds achievable by the method are…

Computational Complexity · Computer Science 2019-12-04 Paul Beame , Nathan Grosshans , Pierre McKenzie , Luc Segoufin

We establish an Ergodic Theorem for lower probabilities, a generalization of standard probabilities widely used in applications. As a by-product, we provide a version for lower probabilities of the Strong Law of Large Numbers.

Functional Analysis · Mathematics 2015-08-07 Simone Cerreia-Vioglio , Fabio Maccheroni , Massimo Marinacci

Probabilistic programming languages (PPLs) are expressive means for creating and reasoning about probabilistic models. Unfortunately hybrid probabilistic programs, involving both continuous and discrete structures, are not well supported by…

Programming Languages · Computer Science 2024-06-25 Poorva Garg , Steven Holtzen , Guy Van den Broeck , Todd Millstein

Through a straightforward Bayesian approach we show that under some general conditions a maximum running time, namely the number of discrete steps performed by a computer program during its execution, can be defined such that the…

History and Overview · Mathematics 2007-05-23 Germano D'Abramo

The termination behavior of probabilistic programs depends on the outcomes of random assignments. Almost sure termination (AST) is concerned with the question whether a program terminates with probability one on all possible inputs.…

Programming Languages · Computer Science 2021-01-29 Marcel Moosbrugger , Ezio Bartocci , Joost-Pieter Katoen , Laura Kovács

Recently, there has been an increasing interest in the bottom-up evaluation of the semantics of logic programs with complex terms. The presence of function symbols in the program may render the ground instantiation infinite, and finiteness…

Logic in Computer Science · Computer Science 2015-10-07 Marco Calautti , Sergio Greco , Francesca Spezzano , Irina Trubitsyna

We give a lower bound for the non-collision probability up to a long time T in a system of n independent random walks with fixed obstacles on the two-dimensional lattice. By `collision' we mean collision between the random walks as well as…

Probability · Mathematics 2007-05-23 A. Gaudilliere

The problems of enumerating lattice walks, with an arbitrary finite set of allowed steps, both in one and two dimensions, where one must always stay in the non-negative half-line and quarter-plane respectively, are used, as case studies, to…

Combinatorics · Mathematics 2015-02-17 Shalosh B. Ekhad , Doron Zeilberger

A model of computation for which reasonable yet still incomplete lower bounds are known is the read-once branching program. Here variants of complexity measures successful in the study of read-once branching programs are defined and…

Computational Complexity · Computer Science 2023-05-22 Yaqiao Li , Pierre McKenzie

We study the design of voting rules in the metric distortion framework. It is known that any deterministic rule suffers distortion of at least $3$, and that randomized rules can achieve distortion strictly less than $3$, often at the cost…

Computer Science and Game Theory · Computer Science 2026-02-10 Ziyi Cai , D. D. Gao , Prasanna Ramakrishnan , Kangning Wang

This paper extends the standard chaining technique to prove excess risk upper bounds for empirical risk minimization with random design settings even if the magnitude of the noise and the estimates is unbounded. The bound applies to many…

Machine Learning · Statistics 2016-09-08 Gábor Balázs , András György , Csaba Szepesvári