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Program Synthesis is the mapping of a specification of what a computer program is supposed to do, into a computer program that does what the specification says to do. This is equivalent to constructing any computer program and a sound proof…

Logic in Computer Science · Computer Science 2015-01-08 Charles Volkstorf

We address the problem of minimizing a smooth function under smooth equality constraints. Under regularity assumptions on these constraints, we propose a notion of approximate first- and second-order critical point which relies on the…

Optimization and Control · Mathematics 2024-01-18 Florentin Goyens , Armin Eftekhari , Nicolas Boumal

Logic program transformation by the unfold/fold method ad- vocates the writing of correct logic programs via the application of some rules to a naive program. This work focuses on how to overcome subgoal- introduction difficulties in…

Programming Languages · Computer Science 2018-10-05 Manuel Hernández

First-order model counting (FOMC) is the problem of counting the number of models of a sentence in first-order logic. Since lifted inference techniques rely on reductions to variants of FOMC, the design of scalable methods for FOMC has…

Logic in Computer Science · Computer Science 2025-06-11 Ananth K. Kidambi , Guramrit Singh , Paulius Dilkas , Kuldeep S. Meel

The two-watched literal scheme, a core component of efficient CDCL (Conflict-Driven Clause Learning) implementations for propositional logic, is extended to first-order logic. Given a set of first-order clauses and a set of ground literals,…

Logic in Computer Science · Computer Science 2026-05-21 Yasmine Briefs , Martin Bromberger , Tobias Gehl , Lorenz Leutgeb , Simon Schwarz , Christoph Weidenbach

We address the problem of complementing higher-order patterns without repetitions of existential variables. Differently from the first-order case, the complement of a pattern cannot, in general, be described by a pattern, or even by a…

Logic in Computer Science · Computer Science 2008-10-22 Alberto Momigliano , Frank Pfenning

Proofs (sequent calculus, natural deduction) and imperative algorithms (pseudocodes) are two well-known coexisting concepts. Then what is their relationship? Our answer is that \[ imperative\ algorithms\ =\ proofs\ with\ cuts \] This…

Logic in Computer Science · Computer Science 2022-02-15 Keehang Kwon , Hyung Joon Kwon

Transformers have shown remarkable performance in both natural language processing (NLP) and computer vision (CV) tasks. However, their real-time inference speed and efficiency are limited due to the inefficiency in Softmax and Layer…

Machine Learning · Computer Science 2025-10-21 Wenxun Wang , Shuchang Zhou , Wenyu Sun , Peiqin Sun , Yongpan Liu

Product formula methods, particularly the second-order Suzuki decomposition, are an important tool for simulating quantum dynamics on quantum computers due to their simplicity and unitarity preservation. While higher-order schemes have been…

Quantum Physics · Physics 2025-05-08 Matthew A Lane , Dan E Browne

Large computer-understandable proofs consist of millions of intermediate logical steps. The vast majority of such steps originate from manually selected and manually guided heuristics applied to intermediate goals. So far, machine learning…

Artificial Intelligence · Computer Science 2017-03-02 Cezary Kaliszyk , François Chollet , Christian Szegedy

Identifying the relationships among program elements is useful for program understanding, debugging, and analysis. One such relationship is synonymy. Function synonyms are functions that play a similar role in code, e.g. functions that…

Software Engineering · Computer Science 2018-02-27 Daniel DeFreez , Aditya V. Thakur , Cindy Rubio-González

This paper seeks to apply categorical logic to the design of artificial intelligent agents that reason symbolically about objects more richly structured than sets. Using Johnstone's sequent calculus of terms- and formulae-in-context, we…

Artificial Intelligence · Computer Science 2025-04-29 Ralph Wojtowicz

Refinement Reflection turns your favorite programming language into a proof assistant by reflecting the code implementing a user-defined function into the function's (output) refinement type. As a consequence, at uses of the function, the…

Programming Languages · Computer Science 2016-10-18 Niki Vazou , Ranjit Jhala

Verifying software correctness has always been an important and complicated task. Recently, formal proofs of critical properties of algorithms and even implementations are becoming practical. Currently, the most powerful automated proof…

Logic in Computer Science · Computer Science 2019-04-10 Michael Raskin , Christoph Welzel

Various feature descriptions are being employed in logic programming languages and constrained-based grammar formalisms. The common notational primitive of these descriptions are functional attributes called features. The descriptions…

cmp-lg · Computer Science 2008-02-03 Rolf Backofen , Gert Smolka

Second-order optimization has been developed to accelerate the training of deep neural networks and it is being applied to increasingly larger-scale models. In this study, towards training on further larger scales, we identify a specific…

Machine Learning · Computer Science 2024-06-11 Satoki Ishikawa , Ryo Karakida

We describe an exact sampler for a simply-typed, first-order functional programming language. Given an acyclic finite automaton, $\alpha_{\varnothing}$, it samples a random function uniformly without replacement from well-typed functions in…

Programming Languages · Computer Science 2025-12-02 Breandan Considine

We give a presentation of Krivine and Parigot's Second-order functional arithmetic in Deduction modulo. Expressing this theory in Deduction modulo sheds light on an original aspect of this theory: the fact that programs are specified, not…

Logic in Computer Science · Computer Science 2023-04-27 Gilles Dowek

We derive normal approximation results for a class of stabilizing functionals of binomial or Poisson point process, that are not necessarily expressible as sums of certain score functions. Our approach is based on a flexible notion of the…

Probability · Mathematics 2022-10-20 Zhaoyang Shi , Krishnakumar Balasubramanian , Wolfgang Polonik

Second-order optimization methods offer notable advantages in training deep neural networks by utilizing curvature information to achieve faster convergence. However, traditional second-order techniques are computationally prohibitive,…

Machine Learning · Computer Science 2024-10-04 James Vo
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