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In this paper, we present some new (in-)tractability results related to the integration problem in subspaces of the Wiener algebra over the $d$-dimensional unit cube. We show that intractability holds for multivariate integration in the…

Computational Complexity · Computer Science 2025-03-06 Josef Dick , Takashi Goda , Kosuke Suzuki

Machine Learning techniques have become pervasive across a range of different applications, and are now widely used in areas as disparate as recidivism prediction, consumer credit-risk analysis and insurance pricing. The prevalence of…

Machine Learning · Computer Science 2020-01-14 Michael Varley , Vaishak Belle

We study multivariate $\boldsymbol{L}_{\infty}$-approximation for a weighted Korobov space of periodic functions for which the Fourier coefficients decay exponentially fast. The weights are defined, in particular, in terms of two sequences…

Numerical Analysis · Mathematics 2016-02-09 Peter Kritzer , Friedrich Pillichshammer , Henryk Wozniakowski

We continue our analysis of the consequences of the commutation relation $[S,T]=\Id$, where $S$ and $T$ are two closable unbounded operators. The {\em weak} sense of this commutator is given in terms of the inner product of the Hilbert…

Mathematical Physics · Physics 2015-06-17 Fabio Bagarello , Atsushi Inoue , Camillo Trapani

The workflow satisfiability problem is concerned with determining whether it is possible to find an allocation of authorized users to the steps in a workflow in such a way that all constraints are satisfied. The problem is NP-hard in…

Cryptography and Security · Computer Science 2012-10-16 J. Crampton , R. Crowston , G. Gutin , M. Jones , M. S. Ramanujan

The theory of computational complexity focuses on functions and, hence, studies programs whose interactive behavior is reduced to a simple question/answer pattern. We propose a broader theory whose ultimate goal is expressing and analyzing…

Computational Complexity · Computer Science 2012-09-05 Ugo Dal Lago , Tobias Heindel , Damiano Mazza , Daniele Varacca

Building on existing work with Hyperblocks, which classify data using minimum and maximum bounds for each attribute, we focus on enhancing interpretability, decreasing training time, and reducing model complexity without sacrificing…

Machine Learning · Computer Science 2025-06-10 Austin Snyder , Ryan Gallagher , Boris Kovalerchuk

Formal explainability guarantees the rigor of computed explanations, and so it is paramount in domains where rigor is critical, including those deemed high-risk. Unfortunately, since its inception formal explainability has been hampered by…

Artificial Intelligence · Computer Science 2024-12-04 Xuanxiang Huang , Joao Marques-Silva

This article generalises the concept of realised covariation to Hilbert-space-valued stochastic processes. More precisely, based on high-frequency functional data, we construct an estimator of the trace-class operator-valued integrated…

Probability · Mathematics 2020-11-30 Fred Espen Benth , Dennis Schroers , Almut E. D. Veraart

In this article, we study parameterized complexity theory from the perspective of logic, or more specifically, descriptive complexity theory. We propose to consider parameterized model-checking problems for various fragments of first-order…

Computational Complexity · Computer Science 2007-05-23 Joerg Flum , Martin Grohe

Literature on Constraint Satisfaction exhibits the definition of several structural properties that can be possessed by CSPs, like (in)consistency, substitutability or interchangeability. Current tools for constraint solving typically…

Artificial Intelligence · Computer Science 2014-01-16 Lucas Bordeaux , Marco Cadoli , Toni Mancini

We are aiming at sharp and explicit-in-dimension estimations of the cardinality of $s$-dimensional hyperbolic crosses where $s$ may be large, and applications in high-dimensional approximations of functions having mixed smoothness. In…

Numerical Analysis · Mathematics 2014-01-24 Alexey Chernov , Dinh Dung

Network or graph structures are ubiquitous in the study of complex systems. Often, we are interested in complexity trends of these system as it evolves under some dynamic. An example might be looking at the complexity of a food web as…

Information Theory · Computer Science 2012-01-23 Russell K. Standish

Numerical differentiation of a function, contaminated with noise, over the unit interval $[0,1] \subset \mathbb{R}$ by inverting the simple integration operator $J:L^2([0,1]) \to L^2([0,1])$ defined as $[Jx](s):=\int_0^s x(t) dt$ is…

Numerical Analysis · Mathematics 2023-05-24 Bernd Hofmann , Hans-Jürgen Fischer , Robert Plato

We propose an extension of the framework for discussing the computational complexity of problems involving uncountably many objects, such as real numbers, sets and functions, that can be represented only through approximation. The key idea…

Computational Complexity · Computer Science 2013-05-03 Akitoshi Kawamura , Stephen Cook

We investigate the computational complexity of problems on toric ideals such as normal forms, Gr\"obner bases, and Graver bases. We show that all these problems are strongly NP-hard in the general case. Nonetheless, we can derive efficient…

Symbolic Computation · Computer Science 2019-02-06 Diego Cifuentes , Shmuel Onn

Pearl's Causal Hierarchy (PCH) is a central framework for reasoning about probabilistic, interventional, and counterfactual statements, yet the satisfiability problem for PCH formulas is computationally intractable in almost all classical…

Artificial Intelligence · Computer Science 2026-01-27 Robert Ganian , Marlene Gründel , Simon Wietheger

In this paper, we study arbitrary infinite binary information systems each of which consists of an infinite set called universe and an infinite set of two-valued functions (attributes) defined on the universe. We consider the notion of a…

Computational Complexity · Computer Science 2022-01-05 Mikhail Moshkov

Consider a multi-class labelling problem, where the labels can take values in $[k]$, and a predictor predicts a distribution over the labels. In this work, we study the following foundational question: Are there notions of multi-class…

Machine Learning · Computer Science 2024-06-11 Parikshit Gopalan , Lunjia Hu , Guy N. Rothblum

A wide range of problems can be modelled as constraint satisfaction problems (CSPs), that is, a set of constraints that must be satisfied simultaneously. Constraints can either be represented extensionally, by explicitly listing allowed…

Artificial Intelligence · Computer Science 2013-07-09 Evgenij Thorstensen