Playlist: 33 videos

Unifying Theory and Experiment for Large-Scale Networks

Nov. 18 – Nov. 21, 2013

Many of the more interesting massive data problems involve data that are at least partially graphical; these include social networks, hyperlinked text, images, web graphs, protein networks and spatial data. This workshop will...

0:6:47

Overview: Network Formation

Ashish Goel, Stanford University
Unifying Theory and Experiment for Large-Scale Networks http://simons.berkeley.edu/talks/overview-network-formation
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0:27:47

Challenges of Modeling Network Formation in Tractable Ways

Arun Chandrasekhar, Stanford University
Unifying Theory and Experiment for Large-Scale Networks http://simons.berkeley.edu/talks/arun-chandrasekhar-2013-11-19
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0:30:35

Issues in Developing Estimable Models of Strategic Network Formation

Matt Jackson, Stanford University
Unifying Theory and Experiment for Large-Scale Networks http://simons.berkeley.edu/talks/matt-jackson-2013-11-19
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0:36:56

Behavioral Experiments in a Network Formation Game

Michael Kearns, University of Pennsylvania
Unifying Theory and Experiment for Large-Scale Networks http://simons.berkeley.edu/talks/michael-kearns-2013-11-19
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0:5:19

Overview: Causality/Experiments

Matt Jackson, Stanford University
Unifying Theory and Experiment for Large-Scale Networks http://simons.berkeley.edu/talks/overview-causalityexperiments
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0:31:28

Are Observational Studies of Social Contagion Doomed?

Cosma Shalizi, Carnegie Mellon University
Unifying Theory and Experiment for Large-Scale Networks http://simons.berkeley.edu/talks/cosma-shalizi-2013-11-19
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0:25:0

On Sampling in Dynamic Networks for Inference, Experiments, and Interventions

Steve Thompson, Simon Fraser University
Unifying Theory and Experiment for Large-Scale Networks http://simons.berkeley.edu/talks/steve-thompson-2013-11-19
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0:30:38

The Effect of Social Media on News Consumption

Markus Mobius, Microsoft Research New England
Unifying Theory and Experiment for Large-Scale Networks http://simons.berkeley.edu/talks/markus-mobius-2013-11-19
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0:1:33

Overview: Label Prediction/Diffusion

Michael Kearns, University of Pennsylvania
Unifying Theory and Experiment for Large-Scale Networks http://simons.berkeley.edu/talks/overview-label-predictiondiffusion
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0:28:1

Semi-supervised Learning on Graphs, Using Observed Correlation Structure

Art Owen, Stanford University
Unifying Theory and Experiment for Large-Scale Networks http://simons.berkeley.edu/talks/art-owen-2013-11-20
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