• Click on the titles of individual talks for abstract, slides and archived video.

All events take place in the Calvin Lab Auditorium.

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Coffee and Check-In
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Opening Remarks
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Overview: Graph Models
Michael Kearns (University of Pennsylvania)
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Limiting Behavior in Large Networks
Patrick Wolfe, University College London
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Practice is Better than Theory: Using Approximate Counting to Mine Large Graphs
Sebastiano Vigna, University of Milan
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Break
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Bayesian Models for Graph Data and the Open Problem of Invariance in Networks
Peter Orbanz, Columbia University
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Know Your Epidemic: But How?
Matt Salganik, Princeton University
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Discussion
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Lunch Break
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Overview: Clustering
Jennifer Neville (Purdue University)
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Asymptotic Analysis of Unlabelled Networks
Peter Bickel (UC Berkeley)
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Finding Small Structures in Large Datasets
Andrea Montanari, Stanford University
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Break
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Local Clustering and the Blessing of Transitivity
Karl Rohe, University of Wisconsin-Madison
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Large-scale Graph Clustering and Message-passing-based Distributed Framework
Vahab Mirrokni, Google
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Discussion
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Coffee and Check-In
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Overview: Network Formation
Ashish Goel (Stanford University)
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Challenges of Modeling Network Formation in Tractable Ways
Arun Chandrasekhar, Stanford University
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Relating Developmental Transcription Factors (TFs) Based on Fruitfly Embryoic Images
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Break
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Issues in Developing Estimable Models of Strategic Network Formation
Matt Jackson (Stanford University)
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Behavioral Experiments in a Network Formation Game
Michael Kearns (University of Pennsylvania)
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Discussion
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Lunch Break
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Overview: Causality/Experiments
Matt Jackson (Stanford University)
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Are Observational Studies of Social Contagion Doomed?
Cosma Shalizi, Carnegie Mellon University
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On Sampling in Dynamic Networks for Inference, Experiments, and Interventions
Steve Thompson, Simon Fraser University
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Break
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The Effect of Social Media on News Consumption
Markus Mobius, Microsoft Research New England
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Discussion
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Reception
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Coffee and Check-In
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Overview: Label Prediction/Diffusion
Michael Kearns (University of Pennsylvania)
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Semi-supervised Learning on Graphs, Using Observed Correlation Structure
Art Owen, Stanford University
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How Predictable are Online Cascades
Lada Adamic, Facebook
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Break
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The Impact of Network Structure on Relational Learning and Inference
Jennifer Neville (Purdue University)
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The Emergence of Convention: An Experimental Study of Social Order
Damon Centola, Massachusetts Institute of Technology
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Discussion
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Lunch Break
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Overview: Networks Over Time
Patrick Wolfe, University College London
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Estimating Time-Varying Networks
Mladen Kolar (University of Chicago)
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Pre-Processing of Dynamic Networks: Its Impact on Analytics
Sofus Macskássy, Facebook
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Break
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Graph Streams and Sketches: What Can and Can't Be Done
Andrew McGregor (University of Massachusetts Amherst)
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The Trials and Tribulations of Tractably Counting Triangles
C. Seshadhri, Sandia National Laboratories
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Discussion
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Coffee and Check-In
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Overview: Scalability/Practical Challenges
Deepak Agarwal (LinkedIn)
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Graph Algorithms for Modern Data Models
Ashish Goel (Stanford University)
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On Unifying Asymptotic Complexity with Real-world Performance in Matrix-based Network Computations
David Gleich (Purdue University)
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Break
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Evolving Graphs
Ravi Kumar, Google
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Theoretical and Practical Challenges of Recommending Content to Users in a Social Network
Deepak Agarwal (LinkedIn)
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Discussion