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Related papers: Implicit complexity via structure transformation

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We apply to logic programming some recently emerging ideas from the field of reduction-based communicating systems, with the aim of giving evidence of the hidden interactions and the coordination mechanisms that rule the operational…

Logic in Computer Science · Computer Science 2007-05-23 Roberto Bruni , Ugo Montanari , Francesca Rossi

Abstraction is one of the fundamental concepts of software design. Consequently, the determination of an appropriate abstraction level for the multitude of artefacts that form a software system is an integral part of software engineering.…

Software Engineering · Computer Science 2017-09-06 Stefan Wagner , Florian Deissenboeck

Although there is a somewhat standard formalization of computability on countable sets given by Turing machines, the same cannot be said about uncountable sets. Among the approaches to define computability in these sets, order-theoretic…

Logic in Computer Science · Computer Science 2022-09-07 Pedro Hack , Daniel A. Braun , Sebastian Gottwald

The rise of multi-paradigm languages challenges traditional classification methods, leading to practical software engineering issues like interoperability defects. This systematic literature review (SLR) maps the formal foundations of…

Programming Languages · Computer Science 2025-08-04 Mikel Vandeloise

Approaching limitations of digital computing technologies have spurred research in neuromorphic and other unconventional approaches to computing. Here we argue that if we want to systematically engineer computing systems that are based on…

Emerging Technologies · Computer Science 2023-08-21 Herbert Jaeger , Beatriz Noheda , Wilfred G. van der Wiel

We provide a unifying framework where artificial neural networks and their architectures can be formally described as particular cases of a general mathematical construction--machines of finite depth. Unlike neural networks, machines have a…

Machine Learning · Computer Science 2022-04-28 Pietro Vertechi , Mattia G. Bergomi

Algorithm extraction aims to synthesize executable programs directly from models trained on algorithmic tasks, enabling de novo algorithm discovery without relying on human-written code. However, applying this paradigm to Transformer is…

Machine Learning · Computer Science 2026-03-20 Yifan Zhang , Wei Bi , Kechi Zhang , Dongming Jin , Jie Fu , Zhi Jin

In the logic programming paradigm, a program is defined by a set of methods, each of which can be executed when specific conditions are met during the current state of an execution. The semantics of these programs can be elegantly…

Logic in Computer Science · Computer Science 2024-10-02 Matteo Acclavio , Roberto Maieli

In program semantics and verification, reasoning about loops is complicated by the need to produce two separate mathematical arguments: an invariant, for functional properties (ignoring termination); and a variant, for termination (ignoring…

Programming Languages · Computer Science 2025-04-14 Bertrand Meyer

The semantics of assignment and mutual exclusion in concurrent and multi-core/multi-processor systems is presented with attention to low level architectural features in an attempt to make the presentation realistic. Recursive functions on…

Discrete Mathematics · Computer Science 2008-10-09 Victor Yodaiken

A rational number can be naturally presented by an arithmetic computation (AC): a sequence of elementary arithmetic operations starting from a fixed constant, say 1. The asymptotic complexity issues of such a representation are studied e.g.…

Computational Complexity · Computer Science 2007-05-23 Sergey P. Tarasov , Mikhail N. Vyalyi

We propose to use Church encodings in typed lambda-calculi as the basis for an automata-theoretic counterpart of implicit computational complexity, in the same way that monadic second-order logic provides a counterpart to descriptive…

Logic in Computer Science · Computer Science 2019-07-02 Lê Thành Dũng Nguyên

A new class of functions is presented. The structure of the algorithm, particularly the selection criteria (branching), is used to define the fundamental property of the new class. The most interesting property of the new functions is that…

Computational Complexity · Computer Science 2020-02-25 Rade Vuckovac

We use fast-growing finite and infinite sequences of natural numbers and more complicated constructs to define models of hypercomputation and interpret non-arithmetic predicates, with the strongest extensions reaching full second order…

Logic · Mathematics 2017-07-19 Dmytro Taranovsky

Formal explainability guarantees the rigor of computed explanations, and so it is paramount in domains where rigor is critical, including those deemed high-risk. Unfortunately, since its inception formal explainability has been hampered by…

Artificial Intelligence · Computer Science 2024-12-04 Xuanxiang Huang , Joao Marques-Silva

There is a lack of formalism for some key foundational concepts in systems engineering. One of the most recently acknowledged deficits is the inadequacy of systems engineering practices for engineering intelligent systems. In our previous…

Artificial Intelligence · Computer Science 2024-09-21 Niloofar Shadab , Tyler Cody , Alejandro Salado , Peter Beling

We are entering a new era in which software systems are becoming more and more complex and larger. So, the composition of such systems is becoming infeasible by manual means. To address this challenge, self-organising software models…

Formal Languages and Automata Theory · Computer Science 2025-08-27 Damian Arellanes

Much algorithmic research in NLP aims to efficiently manipulate rich formal structures. An algorithm designer typically seeks to provide guarantees about their proposed algorithm -- for example, that its running time or space complexity is…

Programming Languages · Computer Science 2025-12-30 Tim Vieira , Ryan Cotterell , Jason Eisner

We propose a method for automatically generating abstract transformers for static analysis by abstract interpretation. The method focuses on linear constraints on programs operating on rational, real or floating-point variables and…

Programming Languages · Computer Science 2008-11-04 David Monniaux

Implicit probabilistic models are a flexible class of models defined by a simulation process for data. They form the basis for theories which encompass our understanding of the physical world. Despite this fundamental nature, the use of…

Machine Learning · Statistics 2017-11-07 Dustin Tran , Rajesh Ranganath , David M. Blei
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