PPT-The Structure of Networks

with emphasis on information and social networks T214SINE Summer 2011 Chapter 7 Ýmir Vigfússon Game theory Regular game theory I ndividual players make decisions P ayoffs depend on decisions made by all. M.E.J. Newman in . PNAS. 2006. 1. Networks. A network: presented by a graph G(. V,E. ):. V = nodes, E = edges (link node pairs). Examples of real-life networks: . social networks (V = people) . World Wide Web (V= . st. Century. Paul Ormerod. www.paulormerod.com. Economic and social policy since 1945. Essentially based on a view that decisions are made ‘rationally’ by people, firms, planners etc . [‘agents’]. Units. IEOR 8100.003 Final Project. 9. th. May 2012. Daniel Guetta. Joint work with Carri Chan. This talk. Hospitals. Bayesian Networks. Data!. Modified EM Algorithm. First results. Instrumental variables. CIS 700/005 . –. Lecture 3. Includes material . from Brighten . Godfrey. Last Time. …. K-. ary. fat tree: three-layer topology (edge, aggregation and core). each pod consists of (k/2). 2. servers & 2 layers of k/2 k-port switches. Blake Shaw, Tony . Jebara. ICML 2009 (Best Student Paper nominee). Presented by Feng Chen. Outline. Motivation. Solution. Experiments. Conclusion. Motivation. Graphs exist everywhere: web link networks, social networks, molecules networks, . Application to voting patterns in the US Senate. Based on . “Sequential . detection of temporal communities . by . estrangement . confinement”. Kawadia. , Sreenivasan, . Sci. Rep. . 1. :794 (2015). By: Ralucca Gera, . Applied math department,. Naval Postgraduate School. Monterey, CA, USA. Why?. Mostly observed real networks have:. Heavy tail (. powerlaw. most probably, exponential). High clustering (high number of triangles especially in social networks, lower count otherwise). Generally a DAG, directed acyclic graph. VisGraph, HKUST. LeNet. AlexNet. ZF Net. GoogLeNet. VGGNet. ResNet. Learned convolutional filters: Stage 1. Visualizing and understanding convolutional neural networks.. Monterey, California. rgera@nps.edu. Overview of. Communities in networks. What is a community?. A community . ~ a group of people with common characteristic or shared interests. What do they correspond to?. Leskovec. Computer Science Department. Cornell University / Stanford University. Today: Rich data. L. arge on-line systems have detailed records of human activity. On-line communities:. Facebook (64 million users, billion dollar business). Monojit . Choudhury. Microsoft Research India. monojitc@microsoft.com. . . light. color. red. blue. blood. sky. heavy. weight. 100. 20. 1. NLP vs. Computational Linguistics. Computational Linguistics is the study of . Discovery, The Challenge of Emergent Truth: . ORNEITA BURTON, ABILENE CHRISTIAN UNIVERSITY. Christian Scholars conference, 2018 . Myth or Fact?. Research Reference. Result?. During the last two decades, the large-scale use of incarceration to solve social problems has combined with the fall-out of globalization to produce an ominous trend: prisons have become a ‘growth industry’ in (rural) America.. IEOR 8100.003 Final Project. 9. th. May 2012. Daniel Guetta. Joint work with Carri Chan. This talk. Hospitals. Bayesian Networks. Data!. Modified EM Algorithm. First results. Instrumental variables. Core-periphery structure. Excellence Through Knowledge. Prof. Ralucca Gera, rgera@nps.edu . Applied Mathematics Department, . Naval Postgraduate School. Learning Outcomes. Understand and contrast the different k-clique relaxation definitions:.