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We show (almost) separation between certain important classes of Boolean functions. The technique that we use is to show that the total influence of functions in one class is less than the total influence of functions in the other class. In…

Computational Complexity · Computer Science 2020-10-23 Aniruddha Biswas , Palash Sarkar

Left-sequential logics provide a means for reasoning about (closed) propositional terms with atomic propositions that may have side effects and that are evaluated sequentially from left to right. Such propositional terms are commonly used…

Logic in Computer Science · Computer Science 2012-06-12 D. J. C. Staudt

We study the problem of cutting a length-$n$ string of positive real numbers into $k$ pieces so that every piece has sum at least $b$. The problem can also be phrased as transforming such a string into a new one by merging adjacent numbers.…

Data Structures and Algorithms · Computer Science 2023-09-29 Yinqi Cai

The number of quantifiers needed to express first-order (FO) properties is captured by two-player combinatorial games called multi-structural games. We analyze these games on binary strings with an ordering relation, using a technique we…

Logic in Computer Science · Computer Science 2025-08-01 Marco Carmosino , Ronald Fagin , Neil Immerman , Phokion Kolaitis , Jonathan Lenchner , Rik Sengupta

Neural algorithmic reasoners are parallel processors. Teaching them sequential algorithms contradicts this nature, rendering a significant share of their computations redundant. Parallel algorithms however may exploit their full…

Machine Learning · Computer Science 2024-01-04 Valerie Engelmayer , Dobrik Georgiev , Petar Veličković

Neural networks are known for their ability to approximate smooth functions, yet they fail to generalize perfectly to unseen inputs when trained on discrete operations. Such operations lie at the heart of algorithmic tasks such as…

Machine Learning · Computer Science 2026-02-03 Artur Back de Luca , George Giapitzakis , Kimon Fountoulakis

We investigate the order of the variance of the optimal alignments score of two independent iid binary random words having the same length. The letters are equiprobable, but the scoring function is such that one letter has a larger score…

Probability · Mathematics 2016-06-17 Christian Houdré , Heinrich Matzinger

Classic algorithms and machine learning systems like neural networks are both abundant in everyday life. While classic computer science algorithms are suitable for precise execution of exactly defined tasks such as finding the shortest path…

Machine Learning · Computer Science 2022-09-02 Felix Petersen

Process equivalences are formal methods that relate programs and system which, informally, behave in the same way. Since there is no unique notion of what it means for two dynamic systems to display the same behaviour there are a multitude…

Logic in Computer Science · Computer Science 2012-10-10 Martin Lange , Etienne Lozes , Manuel Vargas Guzmán

Similarity functions measure how comparable pairs of elements are, and play a key role in a wide variety of applications, e.g., notions of Individual Fairness abiding by the seminal paradigm of Dwork et al., as well as Clustering problems.…

Machine Learning · Computer Science 2023-10-24 Leonidas Tsepenekas , Ivan Brugere , Freddy Lecue , Daniele Magazzeni

Test suites assess natural language processing models' performance on specific functionalities: cases of interest involving model robustness, fairness, or particular linguistic capabilities. This paper introduces specification instructions:…

Computation and Language · Computer Science 2024-11-19 Pedro Henrique Luz de Araujo , Benjamin Roth

It is shown that the length of the algorithmic minimal sufficient statistic of a binary string x, either in a representation of a finite set, computable semimeasure, or a computable function, has a length larger than the computational depth…

Computational Complexity · Computer Science 2009-11-25 Bruno Bauwens

We present several families of total boolean functions which have exact quantum query complexity which is a constant multiple (between 1/2 and 2/3) of their classical query complexity, and show that optimal quantum algorithms for these…

Quantum Physics · Physics 2016-02-24 Ashley Montanaro , Richard Jozsa , Graeme Mitchison

One of the major hurdles toward automatic semantic understanding of computer programs is the lack of knowledge about what constitutes functional equivalence of code segments. We postulate that a sound knowledgebase can be used to…

Programming Languages · Computer Science 2017-05-03 Hasan M. Jamil

We compare different methods for the computation of the real dilogarithm regarding their ability for using instruction-level parallelism when executed on appropriate CPUs. As a result we present an instruction-level-aware method and compare…

High Energy Physics - Phenomenology · Physics 2022-01-06 Alexander Voigt

A new numerical characterization of symbolic sequences is proposed. The partition of sequence based on Ke and Tong algorithm is a starting point. Algorithm decomposes original sequence into set of distinct subsequences - a patterns. The set…

Quantitative Methods · Quantitative Biology 2011-09-08 B. Kozarzewski

We introduce a novel approach to the automated termination analysis of computer programs: we use neural networks to represent ranking functions. Ranking functions map program states to values that are bounded from below and decrease as a…

Machine Learning · Computer Science 2022-09-07 Mirco Giacobbe , Daniel Kroening , Julian Parsert

The focus of these lecture notes is on abstract models and basic ideas and results that relate to the operational semantics of programming languages largely conceived. The approach is to start with an abstract description of the computation…

Programming Languages · Computer Science 2025-10-15 Roberto M. Amadio

In a previous paper, an implementable algorithm was introduced to compute discrete solutions of sweeping processes (i.e. specific first order differential inclusions). The convergence of this numerical scheme was proved thanks to…

Numerical Analysis · Mathematics 2014-03-31 Frederic Bernicot , Juliette Venel

When the distributions of the training and test data do not coincide, the problem of understanding generalization becomes considerably more complex, prompting a variety of questions. Prior work has shown that, for some fixed learning…

Machine Learning · Computer Science 2025-12-03 Jordi Pérez-Guijarro