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 |

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

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