English
Related papers

Related papers: Closure operators: Complexity and applications to …

200 papers

The primary purpose of this paper is to investigate the question of invertibility of the sum of operators. The setting is bounded and unbounded linear operators. Some interesting examples and consequences are given. As an illustrative…

Functional Analysis · Mathematics 2018-10-04 Mohammed Hichem Mortad

We investigate the polynomial closure operation (C -> Pol(C)) defined on classes of regular languages. We present an interesting and useful connection relating the separation problem for the class C and the membership problem for it…

Formal Languages and Automata Theory · Computer Science 2018-02-20 Thomas Place , Marc Zeitoun

The classification of separable operator spaces and systems is commonly believed to be intractable. We analyze this belief from the point of view of Borel complexity theory. On one hand we confirm that the classification problems for…

Operator Algebras · Mathematics 2016-02-22 Martín Argerami , Samuel Coskey , Mehrdad Kalantar , Matthew Kennedy , Martino Lupini , Marcin Sabok

Moment closure methods appear in myriad scientific disciplines in the modelling of complex systems. The goal is to achieve a closed form of a large, usually even infinite, set of coupled differential (or difference) equations. Each equation…

Statistical Mechanics · Physics 2018-12-24 Christian Kuehn

An algorithm to decide the emptiness of a regular type expression with set operators given a set of parameterised type definitions is presented. The algorithm can also be used to decide the equivalence of two regular type expressions and…

Logic in Computer Science · Computer Science 2007-05-23 Lunjin Lu , John G. Cleary

The occurrence of unknown words in texts significantly hinders reading comprehension. To improve accessibility for specific target populations, computational modelling has been applied to identify complex words in texts and substitute them…

Computation and Language · Computer Science 2023-03-10 Kai North , Marcos Zampieri , Matthew Shardlow

In model selection problems for machine learning, the desire for a well-performing model with meaningful structure is typically expressed through a regularized optimization problem. In many scenarios, however, the meaningful structure is…

Optimization and Control · Mathematics 2022-11-09 Jonathan Bunton , Paulo Tabuada

Machine learning (ML) algorithms have become integral to decision making in various domains, including healthcare, finance, education, and law enforcement. However, concerns about fairness and bias in these systems pose significant ethical…

Machine Learning · Computer Science 2024-12-18 Ahmed Rashed , Abdelkrim Kallich , Mohamed Eltayeb

Trust is a crucial factor affecting the adoption of machine learning (ML) models. Qualitative studies have revealed that end-users, particularly in the medical domain, need models that can express their uncertainty in decision-making…

Machine Learning · Computer Science 2023-04-21 Andrew Houston , Georgina Cosma

We define the notion of rational closure in the context of Description Logics extended with a tipicality operator. We start from ALC+T, an extension of ALC with a typicality operator T: intuitively allowing to express concepts of the form…

Artificial Intelligence · Computer Science 2013-05-07 Laura Giordano , Valentina Gliozzi , Nicola Olivetti , Gian Luca Pozzato

Ensembles of classifier models typically deliver superior performance and can outperform single classifier models given a dataset and classification task at hand. However, the gain in performance comes together with the lack in…

Human-Computer Interaction · Computer Science 2017-10-23 Bruno Schneider , Dominik Jäckle , Florian Stoffel , Alexandra Diehl , Johannes Fuchs , Daniel Keim

Deep learning methods have been very effective for a variety of medical diagnostic tasks and has even beaten human experts on some of those. However, the black-box nature of the algorithms has restricted clinical use. Recent explainability…

Computer Vision and Pattern Recognition · Computer Science 2020-05-29 Amitojdeep Singh , Sourya Sengupta , Vasudevan Lakshminarayanan

In this paper, we assess the complexity results of formalisms that describe the feature theories used in computational linguistics. We show that from these complexity results no immediate conclusions can be drawn about the complexity of the…

cmp-lg · Computer Science 2008-02-03 Marten Trautwein

A new class of functions is presented. The structure of the algorithm, particularly the selection criteria (branching), is used to define the fundamental property of the new class. The most interesting property of the new functions is that…

Computational Complexity · Computer Science 2020-02-25 Rade Vuckovac

Biclustering is an unsupervised machine learning technique that simultaneously clusters rows and columns in a data matrix. Biclustering has emerged as an important approach and plays an essential role in various applications such as…

Machine Learning · Computer Science 2022-03-31 Adan Jose-Garcia , Julie Jacques , Vincent Sobanski , Clarisse Dhaenens

Implicit Computational Complexity makes two aspects implicit, by manipulating programming languages rather than models of com-putation, and by internalizing the bounds rather than using external measure. We survey how automata theory…

Logic in Computer Science · Computer Science 2015-02-05 Clément Aubert

We describe a closed operator functional calculus in Banach modules over the group algebra $L^1(\mathbb R)$ and illustrate its usefulness with a few applications. In particular, we deduce a spectral mapping theorem for operators in the…

Functional Analysis · Mathematics 2021-09-06 Anatoly G. Baskakov , Ilya A. Krishtal , Natalia B. Uskova

In this paper we investigate the interplay between isolated suborders and closures. Isolated suborders are a special kind of suborders and can be used to diminish the number of elements of an ordered set by means of a quotient construction.…

Discrete Mathematics · Computer Science 2024-08-07 Roland Glück

Declarative machine learning (ML) aims at the high-level specification of ML tasks or algorithms, and automatic generation of optimized execution plans from these specifications. The fundamental goal is to simplify the usage and/or…

Databases · Computer Science 2016-05-20 Matthias Boehm , Alexandre V. Evfimievski , Niketan Pansare , Berthold Reinwald

Given the importance of integrating of explainability into machine learning, at present, there are a lack of pedagogical resources exploring this. Specifically, we have found a need for resources in explaining how one can teach the…

Human-Computer Interaction · Computer Science 2022-02-22 Andreas Bueff , Ioannis Papantonis , Auste Simkute , Vaishak Belle
‹ Prev 1 8 9 10 Next ›