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Variable environment is the time-honored way of making sense of free variables, used in programming language theory as well when writing interpreters and some compilers. Algebraic effects give another way, as was pointed already at HOPE…

Programming Languages · Computer Science 2023-12-29 Oleg Kiselyov

It is commonly agreed that the success of future proof assistants will rely on their ability to incorporate computations within deduction in order to mimic the mathematician when replacing the proof of a proposition P by the proof of an…

Logic in Computer Science · Computer Science 2007-07-10 Frédéric Blanqui , Jean-Pierre Jouannaud , Pierre-Yves Strub

Sequential effect systems are a class of effect system that exploits information about program order, rather than discarding it as traditional commutative effect systems do. This extra expressive power allows effect systems to reason about…

Programming Languages · Computer Science 2020-05-18 Colin S. Gordon

Deep inference is a proof theoretic methodology that generalizes the standard notion of inference of the sequent calculus, whereby inference rules become applicable at any depth inside logical expressions. Deep inference provides more…

Logic in Computer Science · Computer Science 2015-07-01 Ozan Kahramanogullari

Ordered logics and type systems have been used in a variety of applications including computational linguistics, memory allocation, stream processing, logical frameworks, parametricity, and enforcing security protocols. In most…

Logic in Computer Science · Computer Science 2026-05-20 Sophia Roshal , Frank Pfenning

We present a logical framework for the verification of relational properties in imperative programs. Our work is motivated by relational properties which come from security applications and often require reasoning about formulas with…

Logic in Computer Science · Computer Science 2019-08-13 Gilles Barthe , Renate Eilers , Pamina Georgiou , Bernhard Gleiss , Laura Kovacs , Matteo Maffei

The standard definition of PAC learning (Valiant 1984) requires learners to succeed under all distributions -- even ones that are intractable to sample from. This stands in contrast to samplable PAC learning (Blum, Furst, Kearns, and Lipton…

Computational Complexity · Computer Science 2025-12-02 Guy Blanc , Caleb Koch , Jane Lange , Carmen Strassle , Li-Yang Tan

We assume that every element of a matrix has a small, individual error, and model it by an external number, which is the sum of a nonstandard real number and a neutrix, the latter being a convex (external) set having the group property. The…

Rings and Algebras · Mathematics 2019-07-31 Nam van Tran , Imme van den Berg

We define a bi-directional embedding between hypersequent calculi and a subclass of systems of rules (2-systems). In addition to showing that the two proof frameworks have the same expressive power, the embedding allows for the recovery of…

Logic · Mathematics 2018-05-15 Agata Ciabattoni , Francesco A. Genco

We propose a framework for reasoning about programs that manipulate coinductive data as well as inductive data. Our approach is based on using equational programs, which support a seamless combination of computation and reasoning, and using…

Computational Complexity · Computer Science 2012-01-06 Daniel Leivant , Ramyaa Ramyaa

Type-and-effect systems help the programmer to organize data and computational effects in a program. While for traditional type systems expressive variants with sophisticated inference algorithms have been developed and widely used in…

Programming Languages · Computer Science 2025-10-24 Patrycja Balik , Szymon Jędras , Piotr Polesiuk

We present a calculus providing a Curry-Howard correspondence to classical logic represented in the sequent calculus with explicit structural rules, namely weakening and contraction. These structural rules introduce explicit erasure and…

Logic in Computer Science · Computer Science 2012-03-23 Silvia Ghilezan , Pierre Lescanne , Dragisa Zunic

We define an extension of lambda-calculus with dependents types that enables us to encode transparent and opaque probabilistic programs and prove a strong normalisation result for it by a reducibility technique. While transparent…

Logic in Computer Science · Computer Science 2026-03-10 Francesco A. Genco

Based on an analysis of the inference rules used, we provide a characterization of the situations in which classical provability entails intuitionistic provability. We then examine the relationship of these derivability notions to uniform…

Logic in Computer Science · Computer Science 2016-08-31 Gopalan Nadathur

Inference in expressive probabilistic models is generally intractable, which makes them difficult to learn and limits their applicability. Sum-product networks are a class of deep models where, surprisingly, inference remains tractable even…

Machine Learning · Computer Science 2016-11-14 Abram L. Friesen , Pedro Domingos

We define extrapolation as any type of statistical inference on a conditional function (e.g., a conditional expectation or conditional quantile) evaluated outside of the support of the conditioning variable. This type of extrapolation…

Methodology · Statistics 2024-06-13 Niklas Pfister , Peter Bühlmann

Relation extraction is the task of identifying predefined relationship between entities, and plays an essential role in information extraction, knowledge base construction, question answering and so on. Most existing relation extractors…

Computation and Language · Computer Science 2018-11-12 Liwei Chen , Yansong Feng , Songfang Huang , Bingfeng Luo , Dongyan Zhao

This paper studies useful sharing, which is a sophisticated optimization for lambda-calculi, in the context of call-by-need evaluation in presence of open terms. Useful sharing turns out to be harder in call-by-need than in call-by-name or…

Logic in Computer Science · Computer Science 2021-10-29 Beniamino Accattoli , Maico Leberle

We describe a type system for the linear-algebraic $\lambda$-calculus. The type system accounts for the linear-algebraic aspects of this extension of $\lambda$-calculus: it is able to statically describe the linear combinations of terms…

Logic in Computer Science · Computer Science 2017-05-12 Pablo Arrighi , Alejandro Díaz-Caro , Benoît Valiron

Causal models communicate our assumptions about causes and effects in real-world phe- nomena. Often the interest lies in the identification of the effect of an action which means deriving an expression from the observed probability…

Machine Learning · Statistics 2018-06-20 Santtu Tikka , Juha Karvanen