/Border [ 0 0 0 ] /Border [ 0 0 0 ] You are currently offline. some new models I will suggest. 2.7. /MediaBox [ 0 0 504 858.65000 ] >> /Border [ 0 0 0 ] /pdfrw_0 95 0 R >> /F1 30 0 R Lecture 3: Tuesday Jan 23. 0 858.65000 504 -42.52000 re 504 31.18000 l /A << and quite similar to Durrett section 2.1. /URI (www\056cambridge\056org\0579781107172876) /Resources << /URI (www\056cambridge\056org) Contents List of illustrations xi List of tables xiii Preface xv Course outline xxi Review of undergraduate branching processes, following /ProcSet [ /Text /PDF /ImageI /ImageC /ImageB ] /I1 28 0 R /Rect [ 17.01000 21.01000 191.50000 13.01000 ] /ProcSet [ /Text /PDF /ImageI /ImageC /ImageB ] /URI (www\056cambridge\056org) >> /A << >> << >> Threshold Effects for /Rect [ 17.01000 767.69000 81.07000 759.69000 ] In Complex Networks, three pioneering researchers offer balanced, up-to-date coverage that will be ideal for advanced undergraduates, graduate students, researchers, and industry practitioners alike. The big picture as of year 2001, as sketched in the introduction of the >> >> /ProcSet [ /Text /PDF /ImageI /ImageC /ImageB ] >> /Type /Annot (A. Arenas et al). ET >> /Resources << /Resources << /I1 28 0 R /Contents 110 0 R >> /Parent 1 0 R /pdfrw_0 90 0 R endstream /Border [ 0 0 0 ] /S /URI /Type /Annot /S /URI endobj A Dynamic Model of Social Network Formation Check out these cute /Annots [ << /URI (www\056cambridge\056org\0579781107172876) >> /S /URI /S /URI /pdfrw_0 Do /A << Models and Methods for Random Networks, Lectures 17 - 18: Thursday March 15 and Tuesday March 20. << >> >> /Contents 115 0 R BT stream >> /I1 28 0 R /Rect [ 17.01000 21.01000 191.50000 13.01000 ] Box 513 5600 MB Eindhoven, The Netherlands rhofstad@win.tue.nl January 26, 2013. >> << >> ] /Parent 1 0 R This book aims to explain the basics of graph theory that are needed at an introductory level for students in computer or information sciences. Robert Kleinberg and >> << Based on /Resources << A Comparative Analysis of Influenza Vaccination Programs by stream Contents Preface vii Chapter 1. >> Based on /Parent 1 0 R >> ] /Annots [ << /MediaBox [ 0 0 504 858.65000 ] (P. Holme); /Type /Annot /Type /Annot /Border [ 0 0 0 ] /Type /Page Lecture 1: Tuesday Jan 16. Bollobas: Random Graphs; Janson, Luczak, Rucinski: Random Graphs; Bollobas, Riordan: Percolation. Networks and Complexity in Social Systems. >> /A << /MediaBox [ 0 0 504 858.65000 ] /I1 28 0 R by Josep Diaz, Dieter Mitsche, Xavier Perez. /A << q Graph Theory in the Information Age 1 1.1. >> ] Shankar Bhamidi. /Type /Page Moorea Brega. /S /URI Box 513, 5600 MB Eindhoven, The Netherlands. 0.73700 0.74500 0.75300 rg /Subtype /Link /Resources << f Box 513 5600 MB Eindhoven, The Netherlands rhofstad@win.tue.nl January 27, 2011. /Border [ 0 0 0 ] >> BT Lectures 10 and 11: Tuesday February 20 and Thursday February 22. 141.73000 816.13000 m >> >> /Resources << endobj /Type /Annot /URI (www\056cambridge\056org) Partha Dey. >> << Through examples of large complex graphs in realistic networks, research in graph theory has been forging ahead into exciting new directions. /Font << 2 0 obj >> << Spatial Gossip and Resource Location Protocols by Students taking course for credit need to do one of the following. /URI (www\056cambridge\056org\0579781107172876) /Parent 1 0 R /Border [ 0 0 0 ] Regular Graphs and a Peer-to-Peer Network, Isomorphism and embedding problems for infinite limits of scale-free graphs, The evolution of navigable small-world networks, Near Optimal Routing for Small-World /A << >> << /Annots [ << S >> << 15 0 obj /ExtGState 21 0 R We have included many of the pre-limi /F1 30 0 R /Font << /XObject << /Rect [ 17.01000 767.69000 81.07000 759.69000 ] This approach allows to gradually prepare students for using tools that are necessary to put graph theory to work: complex networks. /F1 30 0 R /S /URI Lecture 25: Thursday April 19. Two Pathogens Spreading on a Network, Whom You Know Matters: Venture Capital Networks and Investment Performance, Cooperation and the Emergence of Role Differentiation in the Dynamics of Social Networks, Maximizing the spread of influence through a social network, Sampling Universal behavior of load distribution in scale-free networks BT /Type /Annot 1 1 1 RG /FormType 1 /XObject << /Subtype /Link A comprehensive introduction to the theory and applications of complex network science, complete with real-world data sets and software tools. ET >> /Count 14 /F1 30 0 R /URI (www\056cambridge\056org) by Lun Li, David Alderson, John C. Doyle, and Walter Willinger. In the second part of the book the student learns about random networks, small worlds, the structure of the Internet and the Web, peer-to-peer systems, and social networks. /Rect [ 17.01000 767.69000 81.07000 759.69000 ] >> q Critical behavior of the Erdos-Renyi random graph: probabilistic methods. Some of my own work, in >> Shweta Bansal, Babak Pourbohloul, Lauren Ancel Meyers; >> << We focus on some of the models that have received the most attention in the literature, namely, the Erdős-Rényi random graph, Inhomogeneous random graphs, the configuration model and preferential attachment models. /Font << Q On the spread /Subtype /Link /Type /Annot Lecture 12: Tuesday February 27. Introduction 1 1.2. 0.99000 w /Type /Annot In this chapter, we draw motivation from real-world networks, and formulate random graph models for them. /S /URI /Type /Annot /Contents 89 0 R /Resources << >> 1 0 obj /S /URI /Border [ 0 0 0 ] (P. Echenique and J. Gomez-Gardenes and Y. Moreno). /Type /XObject /A << /Subtype /Link model of distance. Two Pathogens Spreading on a Network by Mark Newman. Java simulations of the stochastic mean-field The structure and function of complex networks. /pdfrw_0 136 0 R /pdfrw_0 46 0 R Lecture 22: Tuesday April 10. 13 0 obj /Border [ 0 0 0 ] Oskar Sandberg and Ian Clarke. f /Border [ 0 0 0 ] /F1 30 0 R Javed Ahmed. of viruses on the internet by Noam Berger, Christian Borgs, Jennifer T. Chayes, Amin Saberi. /MediaBox [ 0 0 504 858.65000 ] Mathematical results on scale-free random graphs, Networks out of Control: Models and Methods for Random Networks. Jon Kleinberg. as a source for reading projects. Q /URI (www\056cambridge\056org) Dynamics of jamming transitions in complex networks Aan Mad, Max en Lars het licht in mijn leven Ter nagedachtenis aan mijn ouders die me altijd aangemoedigd hebben. >> /Length 13 /Subtype /Link >> /Filter /FlateDecode /Type /Annot /URI (www\056cambridge\056org) /S /URI Random graphs with arbitrary degree distributions and their applications. >> /Rect [ 17.01000 21.01000 191.50000 13.01000 ] <00a900200069006e00200074006800690073002000770065006200200073006500720076006900630065002000430061006d00620072006900640067006500200055006e00690076006500720073006900740079002000500072006500730073> Tj >> Lecture based on Lecture based on q And lecture based on Random Graphs and Complex Networks 1 Branching Processes A branching process is a simple model for something like a population evolving in time. /I1 28 0 R Lectures 4 and 5: Thursday Jan 25 and Tuesday Jan 30. <00430061006d00620072006900640067006500200055006e00690076006500720073006900740079002000500072006500730073> Tj >> /Resources << 17.01000 761.29000 Td Grossglauser, Thiran (EPFL): >> /BBox [ 0 0 504 720 ] /Contents 55 0 R /Contents 94 0 R endobj 0 g /pdfrw_0 116 0 R >> >> ] 10 0 obj The theory of random graphs is widely used to model and analyze most complex networks for studying their behavior and for capturing the uncertainty and the lack of regularity.

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