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It is undecidable in general whether a given finitely presented group is word hyperbolic. We use the concept of pregroups, introduced by Stallings, to define a new class of van Kampen diagrams, which represent groups as quotients of…

Boltzmann samplers and the recursive method are prominent algorithmic frameworks for the approximate-size and exact-size random generation of large combinatorial structures, such as maps, tilings, RNA sequences or various tree-like…

Combinatorics · Mathematics 2017-10-31 Maciej Bendkowski , Olivier Bodini , Sergey Dovgal

We describe a type system with mixed linear and non-linear recursive types called LNL-FPC (the linear/non-linear fixpoint calculus). The type system supports linear typing, which enhances the safety properties of programs, but also supports…

Programming Languages · Computer Science 2023-06-22 Bert Lindenhovius , Michael Mislove , Vladimir Zamdzhiev

We introduce a variant of linear logic with second order quantifiers and type fixpoints, both restricted to purely linear formulas. The Church encodings of binary words are typed by a standard non-linear type `Church,' while the Scott…

Logic in Computer Science · Computer Science 2010-05-05 Aloïs Brunel , Kazushige Terui

We construct a realizability model of linear dependent type theory from a linear combinatory algebra. Our model motivates a number of additions to the type theory. In particular, we add a universe with two decoding operations: one takes…

Logic in Computer Science · Computer Science 2026-02-10 Sam Speight , Niels van der Weide

In this paper we present methods for the synthesis of polynomial invariants for probabilistic transition systems. Our approach is based on martingale theory. We construct invariants in the form of polynomials over program variables, which…

Logic in Computer Science · Computer Science 2019-10-29 Anne Schreuder , C. -H. Luke Ong

Type systems as a way to control or analyze programs have been largely studied in the context of functional programming languages. Some of those work allow to extract from a typing derivation for a program a complexity bound on this…

Logic in Computer Science · Computer Science 2019-10-08 Patrick Baillot , Alexis Ghyselen

We present polygraphic programs, a subclass of Albert Burroni's polygraphs, as a computational model, showing how these objects can be seen as first-order functional programs. We prove that the model is Turing complete. We use polygraphic…

Logic in Computer Science · Computer Science 2008-10-07 Guillaume Bonfante , Yves Guiraud

In this paper we study the expressive power of Horn-formulae in dependence logic and show that they can express NP-complete problems. Therefore we define an even smaller fragment D-Horn* and show that over finite successor structures it…

Logic in Computer Science · Computer Science 2015-07-01 Johannes Ebbing , Juha Kontinen , Julian-Steffen Müller , Heribert Vollmer

This paper investigates what is essentially a call-by-value version of PCF under a complexity-theoretically motivated type system. The programming formalism, ATR, has its first-order programs characterize the polynomial-time computable…

Logic in Computer Science · Computer Science 2017-01-11 Norman Danner , James S. Royer

We show that one can approximate the least fixed point solution for a multivariate system of monotone probabilistic polynomial equations in time polynomial in both the encoding size of the system of equations and in log(1/\epsilon), where…

Computational Complexity · Computer Science 2013-02-21 Kousha Etessami , Alistair Stewart , Mihalis Yannakakis

Many reinforcement learning (RL) environments in practice feature enormous state spaces that may be described compactly by a "factored" structure, that may be modeled by Factored Markov Decision Processes (FMDPs). We present the first…

Machine Learning · Computer Science 2022-03-08 Zihao Deng , Siddartha Devic , Brendan Juba

System F, the polymorphic lambda calculus, features the principle of impredicativity: polymorphic types may be (explicitly) instantiated at other types, enabling many powerful idioms such as Church encoding and data abstraction.…

Programming Languages · Computer Science 2022-03-04 Henry Mercer , Cameron Ramsay , Neel Krishnaswami

This paper provides an alternate characterization of type-two polynomial-time computability, with the goal of making second-order complexity theory more approachable. We rely on the usual oracle machines to model programs with subroutine…

Computational Complexity · Computer Science 2020-10-30 Bruce M. Kapron , Florian Steinberg

In a previous work we introduced Dual Light Affine Logic (DLAL) ([BaillotTerui04]) as a variant of Light Linear Logic suitable for guaranteeing complexity properties on lambda-calculus terms: all typable terms can be evaluated in polynomial…

Logic in Computer Science · Computer Science 2007-05-23 Vincent Atassi , Patrick Baillot , Kazushige Terui

The Koopman framework proposes a linear representation of finite-dimensional nonlinear systems through a generally infinite-dimensional globally linear embedding. Originally, the Koopman formalism has been derived for autonomous systems. In…

Systems and Control · Electrical Eng. & Systems 2025-07-15 Lucian Cristian Iacob , Roland Tóth , Maarten Schoukens

LS is a particular type of computational processes simulating living tissue. They use an unlimited branching process arising from the simultaneous substitutions of some words instead of letters in some initial word. This combines the…

comp-gas · Physics 2007-05-23 Yuri Ozhigov

Girard's Light linear logic (LLL) characterized polynomial time in the proof-as-program paradigm with a bound on cut elimination. This logic relied on a stratification principle and a "one-door" principle which were generalized later…

Logic in Computer Science · Computer Science 2014-05-20 Matthieu Perrinel

Data-driven control of discrete-time and continuous-time systems is of tremendous research interest. In this paper, we explore data-driven optimal control of continuous-time linear systems using input-output data. Based on a density result,…

Optimization and Control · Mathematics 2024-07-18 Philipp Schmitz , Timm Faulwasser , Paolo Rapisarda , Karl Worthmann

For the challenging task of modeling multivariate time series, we propose a new class of models that use dependent Mat\'ern processes to capture the underlying structure of data, explain their interdependencies, and predict their unknown…

Machine Learning · Statistics 2015-02-13 Alexander Vandenberg-Rodes , Babak Shahbaba