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Let XNLP be the class of parameterized problems such that an instance of size n with parameter k can be solved nondeterministically in time $f(k)n^{O(1)}$ and space $f(k)\log(n)$ (for some computable function f). We give a wide variety of…

Computational Complexity · Computer Science 2023-10-24 Hans L. Bodlaender , Carla Groenland , Jesper Nederlof , Céline M. F. Swennenhuis

We reinvestigate known lower bounds for the Intersection Non-Emptiness Problem for Deterministic Finite Automata (DFA's). We first strengthen conditional time complexity lower bounds from T. Kasai and S. Iwata (1985) which showed that…

Formal Languages and Automata Theory · Computer Science 2026-03-24 Michael Wehar

This article discusses ability of Linear Programming models to be used as solvers of NP-complete problems. Integer Linear Programming is known as NP-complete problem, but non-integer Linear Programming problems can be solved in polynomial…

Computational Complexity · Computer Science 2025-10-20 Radoslaw Hofman

The relationship between the complexity classes P and NP is an unsolved question in the field of theoretical computer science. In this paper, we look at the link between the P - NP question and the "Deterministic" versus "Non Deterministic"…

Computational Complexity · Computer Science 2016-03-28 M. Rémon

In this paper, we address complexity issues for timeline-based planning over dense temporal domains. The planning problem is modeled by means of a set of independent, but interacting, components, each one represented by a number of state…

Logic in Computer Science · Computer Science 2018-09-11 Laura Bozzelli , Alberto Molinari , Angelo Montanari , Adriano Peron

This article finds the answer to the question: for any problem from which a non-deterministic algorithm can be derived which verifies whether an answer is correct or not in polynomial time (complexity class NP), is it possible to create an…

Computational Complexity · Computer Science 2024-01-30 Daniel Cardona Delgado

This paper establishes problem-specific sample complexity lower bounds for linear system identification problems. The sample complexity is defined in the PAC framework: it corresponds to the time it takes to identify the system parameters…

Systems and Control · Computer Science 2019-03-26 Yassir Jedra , Alexandre Proutiere

Dynamic nonlinear systems exhibit distortions arising from coupled static and dynamic effects. Their intertwined nature poses major challenges for data-driven modeling. This paper presents a theoretical framework grounded in structured…

Machine Learning · Computer Science 2025-09-23 Sri Satish Krishna Chaitanya Bulusu , Mikko Sillanpää

We study the problem of learning linear temporal logic (LTL) formulas from examples, as a first step towards expressing a property separating positive and negative instances in a way that is comprehensible for humans. In this paper we…

Machine Learning · Computer Science 2023-12-29 Corto Mascle , Nathanaël Fijalkow , Guillaume Lagarde

Error bounds have been studied for more than seventy years, beginning with the seminal result of Hoffman (1952) [{\it J. Res. Natl. Bur. Standards}, 49 (1952), 263--265], which establishes an upper bound for the distance from an arbitrary…

Optimization and Control · Mathematics 2026-05-25 Zhou Wei , Michel Thera , Jen-Chih Yao

With the rapid popularization of big data, the dichotomy between tractable and intractable problems in big data computing has been shifted. Sublinear time, rather than polynomial time, has recently been regarded as the new standard of…

Computational Complexity · Computer Science 2021-12-01 Xiangyu Gao , Jianzhong Li , Dongjing Miao

We examine the minimum amount of memory for real-time, as opposed to one-way, computation accepting nonregular languages. We consider deterministic, nondeterministic and alternating machines working within strong, middle and weak space, and…

Computational Complexity · Computer Science 2013-05-09 Abuzer Yakaryilmaz , A. C. Cem Say

In Descriptive Complexity, there is a vast amount of literature on decision problems, and their classes such as \textbf{P, NP, L and NL}. ~ However, research on the descriptive complexity of optimisation problems has been limited.…

Computational Complexity · Computer Science 2007-05-23 Prabhu Manyem

Originally developed for imputing missing entries in low rank, or approximately low rank matrices, matrix completion has proven widely effective in many problems where there is no reason to assume low-dimensional linear structure in the…

Statistics Theory · Mathematics 2021-05-06 Yunhua Xiang , Tianyu Zhang , Xu Wang , Ali Shojaie , Noah Simon

Hybrid logic with binders is an expressive specification language. Its satisfiability problem is undecidable in general. If frames are restricted to N or general linear orders, then satisfiability is known to be decidable, but of…

Computational Complexity · Computer Science 2012-06-13 Stefan Göller , Arne Meier , Martin Mundhenk , Thomas Schneider , Michael Thomas , Felix Weiss

We present new deterministic algorithms for several cases of the maximum rank matrix completion problem (for short matrix completion), i.e. the problem of assigning values to the variables in a given symbolic matrix as to maximize the…

Data Structures and Algorithms · Computer Science 2014-07-11 Gábor Ivanyos , Marek Karpinski , Nitin Saxena

Satisfiability of Boolean circuits is among the most known and important problems in theoretical computer science. This problem is NP-complete in general but becomes polynomial time when restricted either to monotone gates or linear gates.…

Computational Complexity · Computer Science 2017-10-24 Paweł M. Idziak , Jacek Krzaczkowski

We investigate the correspondence between the time and space recognition complexity of languages. For this purpose, we will code the long-continued computations of deterministic two-tape Turing machines by the relatively short-length…

Computational Complexity · Computer Science 2024-12-24 Ivan V. Latkin

We complete the complexity classification by degree of minimizing a polynomial over the integer points in a polyhedron in $\mathbb{R}^2$. Previous work shows that optimizing a quadratic polynomial over the integer points in a polyhedral…

Optimization and Control · Mathematics 2015-05-07 Alberto Del Pia , Robert Hildebrand , Robert Weismantel , Kevin Zemmer

Savitch showed in $1970$ that nondeterministic logspace (NL) is contained in deterministic $\mathcal{O}(\log^2 n)$ space but his algorithm requires quasipolynomial time. The question whether we can have a deterministic algorithm for every…

Computational Complexity · Computer Science 2016-06-16 Vivek Anand T Kallampally , Raghunath Tewari