NIPS'07 workshop on statistical models of networks

Sat December 8th, 2007, Whistler, BC.
Hilton: Black Tusk room

General information on NIPS workshops

The purpose of the workshop is to bring together people from different disciplines - computer science, statistics, biology, physics, social science, etc - to discuss foundational issues in the modeling of network and relational data. In particular, we hope to discuss various open research issues, such as

• How to represent graphs at varying levels of abstraction, whose topology is potentially condition-specific and time-varying
• How to combine techniques from the graphical model structure learning community with techniques from the statistical network modeling community
• How to integrate relational data with other kinds of data (e.g., gene expression, sequence or text data)

Speaker	Title	Time
.	Opening remarks	7.30-7.35
Stephen Fienberg	Statistical Challenges in Network Modelling (slides)	7.35-8.15
Mark Handcock	Assessing the Goodness-of-Fit of Network Models ( slides) (see also Statistical Models for Social Networks with Application to HIV Epidemiology)	8.15-8.55
.	Poster spotlights 1	8.55-9.15
.	Coffee break	9.15-9.35
Peter Hoff	Hierarchical eigenmodels for pooling relational data (slides)	9.35-10.15
.	Poster spotlights 2	10.15-10.30
.	Skiing/ poster session	10.30-3.00
Jasmine Zhou	Functions and Phenotypes by Integrative Network Analysis (slides)	3.30-4.10
Volker Tresp	Relational Latent Class Models (slides)	4.10-4.50
.	Coffee break	4.50-5.10
Vikash Mansinghka	Efficient Monte Carlo Inference for Infinite Relational Models (slides)	5.10-5.30
.	Discussion	5.30-6.30

Poster spotlights 1

1. A constraint optimization frameworks for efficient inference in hTERGM Amr Ahmed, Eric Xing
2. Statistical discovery of signaling pathways from an ensemble of weakly informative data sources, Edoardo Airoldi, Florian Markowetz, David Blei, Olga Troyanskaya
3. A dynamic theory of social failure in isolated communities, Edoardo Airoldi, David Blei, Eric Xing, Stephen Fienberg
4. Graph reconstruction with degree-constrained subgraphs, Stuart Andrews, Tony Jebara
5. Inferring vertex properties from topology in large networks, Janne Aukia, Samuel Kaski, Janne Sinkkonen
6. Graph clustering, clique matrices and constrained covariances, David Barber
7. Analysing the AS graph instead of just AS graph measurements, Peter Boothe
8. Social media analysis via network approaches, Victor Cheung, Zhi-Li Wu, Chung-hung Li
9. Energy-based factor graphs for prediction in relational data, Sumit Chopra, Yann LeCun
10. Modeling Go positions with planar CRFs, Dmitry Kamenetsky, Nic Schraudolph, Simon Gunter, SVN Vishwanathan

Poster spotlights 2

1. Modeling evolution of ideas in the web of science, Laura Dietz, Steffen Bickel
2. Weak interventions and instrumental variables, Frederick Eberhardt
3. Activity spreading in modula networks, Aram Galstyan, Paul Cohen
4. Network completion and survey sampling, Steve Hanneke and Eric Xing
5. A Bayesian framework for community detection in networks, Jake Hofman, Chris Wiggins
6. Reasoning about large populations with lifted probabilistic inference, Kristian Kersting, Brian Milch, Like Zettlemoyer, Michael Haimes, Leslie Kaelbling
7. Modeling network structure using kronecker multiplication, Jure Leskovec
8. Community-based link prediction with text, David Mimno, Hanna Wallach, Andrew McCallum
9. Non-stationary dynamic Bayesian networks, Joshua Robinson, ALex Hartemink
10. Creating social network models from sensor data, Danny Wyatt, Tanzeem Choudhury, Jeff Bilmes