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Greedy Algorithm for Set Cover in Context of Knowledge Discovery Problems

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Electronic Notes in Theoretical Computer Science 2003年第4期82卷 174-185页

作者： Mikhail Ju. Moshkov Faculty of Computing Mathematics and Cybernetics Nizhny Novgorod State University 23 Gagarina Av. Nizhny Novgorod 603950 Russia

In the paper some problems connected with a process of knowledge discovery are considered. These problems are reduced to the set cover problem. It is known that under a plausible assumption on the class N P the greedy algorithm is close to best approximate polynomial algorithms for the set cover problem solving. Unfortunately, the performance ratio of this algorithm grows almost as natural logarithm on the cardinality of covered set. Instead of usual greedy algorithm we consider greedy algorithm with threshold. This algorithm constructs a partial cover, which covers at least a fixed part (for example, 90%) of the set. We prove that the cardinality of constructed partial cover is bounded from above by a linear function on the minimal cardinality of exact cover C min . In the case of 90% -cover, for example, in the capacity of such function we can take the function 2.31,·,C min +1. This bound is independent of the cardinality of covered set. Notice that the concept of partial cover in context of knowledge discovery problems is very close to the concept of approximate reduct.

关键词： Data table knowledge discovery greedy algorithm partial cover

Towards combining SOA, web2.0 and intelligent agents in virtual organizations

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Towards combining SOA, web2.0 and intelligent agents in virt...

5th European and Mediterranean Conference on Information Systems, EMCIS 2008

作者： Ignatiadis, Ioannis Svirskas, Adomas Vokrínek, Jirí Briggs, Jonathan Centre for Applied Research in Information Systems Faculty of Computing Information Systems and Mathematics Kingston University United Kingdom Department of Cybernetics Gerstner Laboratory for Intelligent Decision Making and Control Czech Technical University Czech Republic

ISBN: (纸本)9781902316581

Service-Oriented Architectures (SOAs) enable businesses to flexibly address their current and future needs in an agile manner. This is achieved by organizing their software assets as interoperable services, which can be flexibly, cost-effectively and timely combined to form business processes according to business requirements. A SOA approach however can also benefit Virtual Organizations (VOs), by enabling participant companies to increase their responsiveness and adaptability with regards to addressing a collaborative business opportunity. Value can also be added to the operations of such a VO with the use of Web2.0 concepts, as well as Intelligent Agents to automate the processes of finding collaborating partners and negotiating the creation of VOs, based on user-defined business rules. This paper discusses the combination of concepts and their potential benefits for Virtual Organizations, based on the ongoing work of a European Union co-funded Information Society Technologies (IST) project. Although at the time of writing of this paper the practical benefits of this approach are still in the evaluation phase, this paper discusses the main ideas and the expected contributions of such an approach.

关键词： Information services

Parallel structure of algorithms and training computational technology specialists

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Parallel structure of algorithms and training computational ...

International Scientific Conference on Informatics 2018: Problems, Methodologies and Technologies, IPMT 2018

作者： Antonov, A.S. Voevodin, V.V. Popova, N.N. Research Computing Center Lomonosov Moscow State University Leninskie gory bld. 4 Moscow119234 Russia Faculty of Computational Mathematics and Cybernetics Lomonosov Moscow State University Leninskie gory bld. 52 Moscow119991 Russia

A universal method for describing an algorithm's parallel structure was developed as a part of AlgoWiki Open Encyclopedia of Parallel Algorithmic Features. AlgoWiki is not just an important source of information on specific algorithms, but also a good training ground for students. To develop a high-quality algorithm description, one needs to study its structure, identify its key properties, obtain the data by practical experiments on a supercomputer and learn to visualize the results. This article describes the experience of conducting a computer lab course on parallel algorithm structure at the faculty of Computational mathematics and cybernetics at Lomonosov Moscow State University. © Published under licence by IOP Publishing Ltd.

关键词： Supercomputers

An Approach for Analyzing Influence Factors on Performance of Implementations of Standard Algorithms

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An Approach for Analyzing Influence Factors on Performance o...

IEEE Region 8 International Conference on Computational Technologies in Electrical and Electronics Engineering, SIBIRCON

作者： Artem Zheltkov Dmitry Nikitenko Faculty of Computation Mathematics and Cybernetics Lomonosov Moscow State University Moscow Russia Research Computing Center Lomonosov Moscow State University Moscow Russia

This paper illustrates the approach for inspecting factors of hardware details and computing problems that impact the performance of typical computing applications and for estimating its influence. The approach extends the idea of supercomputing lists (like TOP500, Graph500, HPCG and others) and combines it with researching algorithms properties (given by AlgoWiki). Possible applications of the approach are described and the main principles of the implementation are given.

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FIESTA5: Numerical high-performance Feynman integral evaluation

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arXiv 2021年

作者： Smirnov, Alexander V. Shapurov, N.D. Vysotsky, L.I. Research Computing Center Moscow State University Moscow Russia Faculty of Computational Mathematics and Cybernetics Moscow State University Moscow Russia Moscow Center for Fundamental and Applied Mathematics Moscow Russia

In this paper we present a new release of the FIESTA program (Feynman Integral Evaluation by a Sector decomposiTion Approach). FIESTA5 is performance-oriented — we implemented improvements of various kinds in order to make Feynman integral evaluation faster. We plugged in two new integrators, the Quasi Monte Carlo and Tensor Train. At the same time the old code of FIESTA4 was upgraded to the C++17 standard and mostly rewritten without self-made structures such as hash tables. There are also several essential improvements which are most relevant for complex integrations — the new release is capable of producing results where previously impossible. Copyright © 2021, The Authors. All rights reserved.

关键词： Quantum theory

Using a Saliency-Driven Convolutional Neural Network Framework for Brain Tumor Detection 22

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Using a Saliency-Driven Convolutional Neural Network Framewo...

6th International Conference on Medical and Health Informatics, ICMHI 2022

作者： Oliveira, Paulo Henrique De C. Farias, Mylène C.Q. Ferreira, Daniel S. Krylov, Andrey S. Ding, Yong Department of Electrical Engineering University of Brasilia Brasília DF Brazil Department of Computing Science Instituto Federal de Education Ciencia e Tecnologia Do Ceara CE Fortaleza Brazil Faculty of Computational Mathematics and Cybernetics Lomonosov Moscow State University Moscow Russia College of Information Science and Electronic Engineering Zhejiang University Zhejiang China

ISBN: (纸本)9781450396301

The process of diagnosing brain tumors from magnetic resonance imaging (MRI) is often time-consuming. Thus, a rapid analyses through an automated system could help improve the treatment possibilities and optimize hospital resources. This paper proposes a method for the classification of brain tumors by means of pre-selecting the tumor region. We estimate the region of interest using attention algorithms and input it to a neural network that classifies the regions as tumoral and non-tumoral. Pre-selecting the region of interest, instead of using the entire image, produced a final classification accuracy of 91.68%, 92.58%, 92.69%, and 93.4% with the models Resnet18, Resnet34, VGG16, and Alexnet, respectively. Once the dimensional space of the input image is reduced, the neural networks is able to capture additional details of the tumor regions during the training stage. This study demonstrates the importance of saliency maps for identifying tumor regions in magnetic resonance images. © 2022 ACM.

关键词： Magnetic resonance imaging

FIRE6: Feynman integral reduction with modular arithmetic

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arXiv 2019年

作者： Smirnov, A.V. Chukharev, F.S. Research Computing Center Moscow State University Moscow119992 Russia Karlsruhe76128 Germany Faculty of Computational Mathematics and Cybernetics Moscow State University Moscow119992 Russia

FIRE is a program performing reduction of Feynman integrals to master integrals. The C++ version of FIRE was presented in 2014. There have been multiple changes and upgrades since then including the possibility to use multiple computers for one reduction task and to perform reduction with modular arithmetic. The goal of this paper is to present the current version of FIRE. Copyright © 2019, The Authors. All rights reserved.

关键词： Quantum theory

Active exploration for body model learning through self-touch on a humanoid robot with artificial skin

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arXiv 2020年

作者： Gama, Filipe Shcherban, Maksym Rolf, Matthias Hoffmann, Matej Department of Cybernetics Faculty of Electrical Engineering Czech Technical University in Prague Prague Czech Republic School of Engineering Computing and Mathematics Oxford Brookes University Oxford United Kingdom

The mechanisms of infant development are far from understood. Learning about one’s own body is likely a foundation for subsequent development. Here we look specifically at the problem of how spontaneous touches to the body in early infancy may give rise to first body models and bootstrap further development such as reaching competence. Unlike visually elicited reaching, reaching to own body requires connections of the tactile and motor space only, bypassing vision. Still, the problems of high dimensionality and redundancy of the motor system persist. In this work, we present an embodied computational model on a simulated humanoid robot with artificial sensitive skin on large areas of its body. The robot should autonomously develop the capacity to reach for every tactile sensor on its body. To do this efficiently, we employ the computational framework of intrinsic motivations and variants of goal babbling—as opposed to motor babbling—that prove to make the exploration process faster and alleviate the ill-posedness of learning inverse kinematics. Based on our results, we discuss the next steps in relation to infant studies: what information will be necessary to further ground this computational model in behavioral data. Copyright © 2020, The Authors. All rights reserved.

关键词： Anthropomorphic robots

Tensor-train numerical integration of multivariate functions with singularities

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arXiv 2021年

作者： Vysotsky, Lev I. Smirnov, Alexander V. Tyrtyshnikov, Eugene E. HSE University Russia Faculty of Computational Mathematics and Cybernetics Moscow State University Russia Moscow Center for Fundamental and Applied Mathematics Russia Research Computing Center Moscow State University Russia Marchuk Institute of Numerical Mathematics Russian Academy of Sciences Russia

Numerical integration is a classical problem emerging in many fields of science. Multivariate integration cannot be approached with classical methods due to the exponential growth of the number of quadrature nodes. We propose a method to overcome this problem. Tensor-train decomposition of a tensor approximating the integrand is constructed and used to evaluate a multivariate quadrature formula. We show how to deal with singularities in the integration domain and conduct theoretical analysis of the integration accuracy. The reference open-source implementation is *** Codes 26B15, 15A69 © 2021, CC BY.

关键词： Tensors