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Computational Aspects and Applications in Large-Scale Networks

NET 2017, Nizhny Novgorod, Russia, June 2017

  • Conference proceedings
  • © 2018

Overview

Editors:
  1. Valery A. Kalyagin

    1. Higher School of Economics, National Research University, Nizhny Novgorod, Russia

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  2. Panos M. Pardalos

    1. Department of Industrial and Systems Engineering, University of Florida, Gainesville, USA

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  3. Oleg Prokopyev

    1. Department of Industrial Engineering, University of Pittsburgh, Pittsburgh, USA

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  4. Irina Utkina

    1. Higher School of Economics, National Research University, Nizhny Novgorod, Russia

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  • Presents state-of-the-art techniques in modern network analysis for large-scale networks
  • Features new theoretical models, approaches, and tools for network analysis
  • Broadens understanding of computationally efficient algorithms

Part of the book series: Springer Proceedings in Mathematics & Statistics (PROMS, volume 247)

Included in the following conference series:

Conference proceedings info: NET 2018.

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Table of contents (26 papers)

  1. Front Matter

    Pages i-xvii
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  2. Network Computational Algorithms

    1. Front Matter

      Pages 1-1
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    2. Tabu Search for Fleet Size and Mix Vehicle Routing Problem with Hard and Soft Time Windows

      • Mikhail Batsyn, Ilya Bychkov, Larisa Komosko, Alexey Nikolaev
      Pages 3-18

    3. FPT Algorithms for the Shortest Lattice Vector and Integer Linear Programming Problems

      • D. V. Gribanov
      Pages 19-35

    4. The Video-Based Age and Gender Recognition with Convolution Neural Networks

      • Angelina S. Kharchevnikova, Andrey V. Savchenko
      Pages 37-46

    5. On Forbidden Induced Subgraphs for the Class of Triangle-König Graphs

      • Dmitry B. Mokeev
      Pages 47-56

    6. The Global Search Theory Approach to the Bilevel Pricing Problem in Telecommunication Networks

      • Andrei V. Orlov
      Pages 57-73

    7. Graph Dichotomy Algorithm and Its Applications to Analysis of Stocks Market

      • Alexander Rubchinsky
      Pages 75-111

    8. Cluster Analysis of Facial Video Data in Video Surveillance Systems Using Deep Learning

      • Anastasiia D. Sokolova, Andrey V. Savchenko
      Pages 113-120

    9. Using Modular Decomposition Technique to Solve the Maximum Clique Problem

      • Irina Utkina
      Pages 121-131

  3. Network Models

    1. Front Matter

      Pages 133-133
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    2. Robust Statistical Procedures for Testing Dynamics in Market Network

      • A. P. Koldanov, M. A. Voronina
      Pages 135-142

    3. Application of Market Models to Network Equilibrium Problems

      • Igor Konnov
      Pages 143-160

    4. Selective Bi-coordinate Variations for Network Equilibrium Problems with Mixed Demand

      • Igor Konnov, Olga Pinyagina
      Pages 161-170

    5. Developing a Model of Topological Structure Formation for Power Transmission Grids Based on the Analysis of the UNEG

      • Sergey Makrushin
      Pages 171-188

    6. Methods of Criteria Importance Theory and Their Software Implementation

      • Andrey Pavlovich Nelyubin, Vladislav Vladimirovich Podinovski, Mikhail Andreevich Potapov
      Pages 189-196

    7. A Model of Optimal Network Structure for Decentralized Nearest Neighbor Search

      • Alexander Ponomarenko, Irina Utkina, Mikhail Batsyn
      Pages 197-203

    8. Computational Study of Activation Dynamics on Networks of Arbitrary Structure

      • Alexander Semenov, Dmitry Gorbatenko, Stepan Kochemazov
      Pages 205-220

    9. Rejection Graph for Multiple Testing of Elliptical Model for Market Network

      • D. P. Semenov, Petr A. Koldanov
      Pages 221-234

    10. Mapping Paradigms of Social Sciences: Application of Network Analysis

      • Dmitry Zaytsev, Daria Drozdova
      Pages 235-253
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Other volumes

  1. Models, Algorithms, and Technologies for Network Analysis

  2. Computational Aspects and Applications in Large-Scale Networks

  3. Network Algorithms, Data Mining, and Applications

Keywords

About this book

Contributions in this volume focus on computationally efficient algorithms and rigorous mathematical theories for analyzing large-scale networks. Researchers and students in mathematics, economics, statistics, computer science and engineering will find this collection a valuable resource filled with the latest research in network analysis. Computational aspects and applications of large-scale networks in market models, neural networks, social networks, power transmission grids, maximum clique problem, telecommunication networks, and complexity graphs are included with new tools for efficient network analysis of large-scale networks.

This proceeding is a result of the 7th International Conference in Network Analysis, held at the Higher School of Economics, Nizhny Novgorod in June 2017. The conference brought together scientists, engineers, and researchers from academia, industry, and government.

Editors and Affiliations

  • Higher School of Economics, National Research University, Nizhny Novgorod, Russia

    Valery A. Kalyagin, Irina Utkina

  • Department of Industrial and Systems Engineering, University of Florida, Gainesville, USA

    Panos M. Pardalos

  • Department of Industrial Engineering, University of Pittsburgh, Pittsburgh, USA

    Oleg Prokopyev

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