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We develop a complexity theory for approximate real computations. We first produce a theory for exact computations but with condition numbers. The input size depends on a condition number, which is not assumed known by the machine. The…

Computational Complexity · Computer Science 2020-05-05 Gregorio Malajovich , Mike Shub

Linear differential equations and recurrences reveal many properties about their solutions. Therefore, these equations are well-suited for representing solutions and computing with special functions. We identify a large class of existing…

Symbolic Computation · Computer Science 2026-01-14 Louis Gaillard

In the area of beyond-planar graphs, i.e. graphs that can be drawn with some local restrictions on the edge crossings, the recognition problem is prominent next to the density question for the different graph classes. For 1-planar graphs,…

Data Structures and Algorithms · Computer Science 2021-08-04 Henry Förster , Michael Kaufmann , Chrysanthi N. Raftopoulou

The class XNLP consists of (parameterized) problems that can be solved nondeterministically in $f(k)n^{O(1)}$ time and $f(k)\log n$ space, where $n$ is the size of the input instance and $k$ the parameter. The class XALP consists of…

Computational Complexity · Computer Science 2025-01-09 Hans L. Bodlaender , Krisztina Szilágyi

Complexity theory can be viewed as the study of the relationship between computation and applications, understood the former as complexity classes and the latter as problems. Completeness results are clearly central to that view. Many…

Logic in Computer Science · Computer Science 2020-09-10 Flavio Ferrarotti , Senen Gonzalez , Klaus-Dieter Schewe , Jose Maria Turull-Torres

We study several variants of decomposing a symmetric matrix into a sum of a low-rank positive semidefinite matrix and a diagonal matrix. Such decompositions have applications in factor analysis and they have been studied for many decades.…

Optimization and Control · Mathematics 2023-10-02 Levent Tunçel , Stephen A. Vavasis , Jingye Xu

Assuming that P is not equal to NP, the worst-case run time of any algorithm solving an NP-complete problem must be super-polynomial. But what is the fastest run time we can get? Before one can even hope to approach this question, a more…

Data Structures and Algorithms · Computer Science 2026-01-09 Jesper Nederlof

We introduce a parallel machine scheduling problem in which the processing times of jobs are not given in advance but are determined by a system of linear constraints. The objective is to minimize the makespan, i.e., the maximum job…

Data Structures and Algorithms · Computer Science 2015-10-30 Kameng Nip , Zhenbo Wang , Zizhuo Wang

In connection with machine arithmetic, we are interested in systems of constraints of the form x + k \leq y + k'. Over integers, the satisfiability problem for such systems is polynomial time. The problem becomes NP complete if we restrict…

Computational Complexity · Computer Science 2008-11-07 Nikolaj Bjørner , Andreas Blass , Yuri Gurevich , Madan Musuvathi

By topological arguments, we prove new results on the existence, non-existence, localization and multiplicity of nontrivial solutions of a class of perturbed nonlinear integral equations. These type of integral equations arise, for example,…

Classical Analysis and ODEs · Mathematics 2021-02-09 Alberto Cabada , Gennaro Infante , F. Adrián F. Tojo

A number of recent papers -- e.g. Brandt et al. (STOC 2016), Chang et al. (FOCS 2016), Ghaffari & Su (SODA 2017), Brandt et al. (PODC 2017), and Chang & Pettie (FOCS 2017) -- have advanced our understanding of one of the most fundamental…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-04-06 Alkida Balliu , Juho Hirvonen , Janne H. Korhonen , Tuomo Lempiäinen , Dennis Olivetti , Jukka Suomela

We show that a wide range of overdetermined boundary problems for semilinear equations with position-dependent nonlinearities admits nontrivial solutions. The result holds true both on the Euclidean space and on compact Riemannian…

Analysis of PDEs · Mathematics 2017-11-27 Miguel Dominguez-Vazquez , Alberto Enciso , Daniel Peralta-Salas

We show that if the probabilistic logarithmic-space solver or the deterministic nearly logarithmic-space solver for undirected Laplacian matrices can be extended to solve slightly larger subclasses of linear systems, then they can be use to…

Computational Complexity · Computer Science 2020-03-17 Xuangui Huang

We consider the problem of learning temporal logic formulas from examples of system behavior. Learning temporal properties has crystallized as an effective mean to explain complex temporal behaviors. Several efficient algorithms have been…

Logic in Computer Science · Computer Science 2024-08-09 Benjamin Bordais , Daniel Neider , Rajarshi Roy

In this paper we study the complexity of the problems: given a loop, described by linear constraints over a finite set of variables, is there a linear or lexicographical-linear ranking function for this loop? While existence of such…

Programming Languages · Computer Science 2025-09-30 Amir M. Ben-Amram , Samir Genaim

We study the quadratic residue problem known as an NP complete problem by way of the prime number and show that a nondeterministic polynomial process does not belong to the class P because of a random distribution of solutions for the…

General Mathematics · Mathematics 2012-12-29 Minoru Fujimoto , Kunihiko Uehara

We prove lower bounds of order $n\log n$ for both the problem to multiply polynomials of degree $n$, and to divide polynomials with remainder, in the model of bounded coefficient arithmetic circuits over the complex numbers. These lower…

Computational Complexity · Computer Science 2007-05-23 Peter Buergisser , Martin Lotz

While several classes of integer linear optimization problems are known to be solvable in polynomial time, far fewer tractability results exist for integer nonlinear optimization. In this work, we narrow this gap by identifying a broad…

Optimization and Control · Mathematics 2026-02-09 Alberto Del Pia

We study classification problems using binary estimators where the decision boundary is described by horizon functions and where the data distribution satisfies a geometric margin condition. A key novelty of our work is the derivation of…

Machine Learning · Statistics 2026-03-16 Jonathan García , Philipp Petersen

We consider several subgroup-related algorithmic questions in groups, modeled after the classic computational lattice problems, and study their computational complexity. We find polynomial time solutions to problems like finding a subgroup…

Group Theory · Mathematics 2015-08-12 Alexei Myasnikov , Andrey Nikolaev , Alexander Ushakov