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The programming language Prolog makes declarative programming possible, at least to a substantial extent. Programs may be written and reasoned about in terms of their declarative semantics. All the advantages of declarative programming are…

Logic in Computer Science · Computer Science 2023-08-31 Włodzimierz Drabent

The minimization of convex functions which are only available through partial and noisy information is a key methodological problem in many disciplines. In this paper we consider convex optimization with noisy zero-th order information,…

Machine Learning · Computer Science 2016-05-27 Francis Bach , Vianney Perchet

We study a well-known technique of using absoluteness for giving choice-free proofs to some statements which are known to be provable with the axiom of choice. The idea is to reduce the problem to an inner model where the axiom of choice…

Logic · Mathematics 2014-02-20 Asaf Karagila

Probabilistic programming languages represent complex data with intermingled models in a few lines of code. Efficient inference algorithms in probabilistic programming languages make possible to build unified frameworks to compute…

Machine Learning · Statistics 2016-07-15 Anh Tong , Jaesik Choi

We introduce a new criterion, replacement freeness, to discern the relative expressiveness of process calculi. Intuitively, a calculus is strongly replacement free if replacing, within an enclosing context, a process that cannot perform any…

Logic in Computer Science · Computer Science 2010-12-01 Federico Banti , Rosario Pugliese , Francesco Tiezzi

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

The problem of combinatorial filter reduction arises from questions of resource optimization in robots; it is one specific way in which automation can help to achieve minimalism, to build better, simpler robots. This paper contributes a new…

Robotics · Computer Science 2022-02-22 Yulin Zhang , Dylan A. Shell

In this article, we consider for the first time the operations of insertion and deletion working in a matrix controlled manner. We show that, similarly as in the case of context-free productions, the computational power is strictly…

Formal Languages and Automata Theory · Computer Science 2010-12-24 Ion Petre , Sergey Verlan

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

Predictive models are fundamental to engineering reliable software systems. However, designing conservative, computable approximations for the behavior of programs (static analyses) remains a difficult and error-prone process for modern…

Programming Languages · Computer Science 2011-05-10 David Van Horn , Matthew Might

Data trees serve as an abstraction of structured data, such as XML documents. A number of specification formalisms for languages of data trees have been developed, many of them adhering to the paradigm of register automata, which is based…

Formal Languages and Automata Theory · Computer Science 2024-07-12 Simon Prucker , Lutz Schröder

Recent developments in termination analysis for declarative programs emphasize the use of appropriate models for the logical theory representing the program at stake as a generic approach to prove termination of declarative programs. In…

Programming Languages · Computer Science 2015-12-23 Salvador Lucas

We revisit evaluation of logical formulas that allow both uninterpreted relations, constrained to be finite, as well as an interpreted vocabulary over an infinite domain. This formalism was denoted embedded finite model theory in the past.…

Logic in Computer Science · Computer Science 2024-05-22 Michael Benedikt , Ehud Hrushovski

The s-semantics makes it possible to explicitly deal with variables in program answers. So it seems suitable for programs using nonground data structures, like open lists. However it is difficult to find published examples of using the…

Logic in Computer Science · Computer Science 2021-08-31 Włodzimierz Drabent

We present a new approach to automated reasoning about higher-order programs by extending symbolic execution to use behavioral contracts as symbolic values, enabling symbolic approximation of higher-order behavior. Our approach is based on…

Programming Languages · Computer Science 2012-04-27 Sam Tobin-Hochstadt , David Van Horn

We present a novel and well automatable approach to formal verification of programs with underspecified semantics, i.e., a language semantics that leaves open the order of certain evaluations. First, we reduce this problem to…

Programming Languages · Computer Science 2022-02-14 Eduard Kamburjan , Nathan Wasser

A circular program creates a data structure whose computation depends upon itself or refers to itself. The technique is used to implement the classic data structures circular and doubly-linked lists, threaded trees and queues, in a…

Programming Languages · Computer Science 2024-03-05 Lloyd Allison

Program slicing provides explanations that illustrate how program outputs were produced from inputs. We build on an approach introduced in prior work by Perera et al., where dynamic slicing was defined for pure higher-order functional…

Programming Languages · Computer Science 2017-09-12 Wilmer Ricciotti , Jan Stolarek , Roly Perera , James Cheney

Demonic composition, demonic refinement and demonic union are alternatives to the usual "angelic" composition, angelic refinement (inclusion) and angelic (usual) union defined on binary relations. We first motivate both the angelic and…

Logic in Computer Science · Computer Science 2021-01-14 Robin Hirsch , Szabolcs Mikulás , Tim Stokes

Generalization error defines the discriminability and the representation power of a deep model. In this work, we claim that feature space design using deep compositional function plays a significant role in generalization along with…

Machine Learning · Computer Science 2017-07-11 Mrinal Haloi
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