Berkeley/CeMMAP Conference on Networks
We are very excited to welcome conference attendees to Berkeley on November 4th and 5th. A preliminary conference program can be found below. Please contact Bryan Graham with any corrections or possible scheduling conflicts. If we have forgetten someone please let us know and we will do our best to make adjustments.
We’ve got a great group of speakers, from the statistics, econometrics and machine learning communities, scheduled.
The conference will be held in Blum Hall Plaza at UC Berkeley. The venue is very close to the North Gate of campus. The nearest BART stop is Downtown Berkeley. The nearest public parking facility is the Lower Hearst / North Gate parking garage at the intersection of Scenic & Hearst (enter from Scenic to access hourly parking spaces).
If you have any logistical questions please write Eric Auerbach. I will post additional information to this page over the coming weeks.
IMPORTANT: We have allocated 40 minutes for each talk. Please anticipate questions from the audience when planning your talk. You are very welcome to use less than forty minutes and decidely not welcome to use more!
Provisional Schedule
Organizers
Aureo de Paula
Bryan Graham
Jasjeet Sekhon
Friday, November 4th, 2016
| Time | Speaker | Title |
|---|---|---|
| 11:40 to 12:30PM | Registration & Lunch | |
| Session 1: Block models & Heterogeneity | ||
| 12:30 to 1:10PM | Peter Bickel (Berkeley) | Block Models with Covariates: Likelihood Methods of Fitting (joint with Purna Sarkar, U.T. Austin, Soumendu Mukherjee, Berkeley, and Sharmodeep Bhattacharyya, Oregon State) |
| 1:10 to 1:50PM | Stephane Bonhomme (Chicago) | Discretizing Unobserved Heterogeneity (joint with Thibaut Lamadon, Chicago, and Elena Manresa, NYU) |
| 1:50 to 2:10PM | Coffee Break | |
| Session 2: Dynamic models | ||
| 2:10 to 2:50PM | Angelo Mele (Hopkins) | Variational Approximations for Large Strategic ERGMs |
| 2:50 to 3:30PM | Peter Hoff (Duke) | Tensor Regression for Dynamic Network Data |
| 3:30 to 3:50PM | Coffee Break | |
| Session 3: Experiments & Spillovers | ||
| 3:50 to 4:30PM | Edoardo M. Airoldi (Harvard) | Two Model-Assisted Strategies for Designing Experiments on Networks |
| 4:30 to 5:10PM | Dean Eckles (MIT) | Estimating Peer Effects in Social Networks with Peer Encouragement Designs (joint with René Kizilcec, Stanford, and Eytan Bakshy, Facebook |
| 5:10 to 5:50PM | Chris Rose (Toulouse) | Social Effects when the Network is Unobserved and Sparse (joint with Eric Gautier, Toulouse) |
| 6:45PM | Speakers’ dinner1 at Soi 4 5421 College Avenue, Oakland, CA 94618 |
Saturday, November 5th, 2016
| Time | Speaker | Title |
|---|---|---|
| 8:30 to 9:00AM | Breakfast | |
| Session 4: Strategic interaction | ||
| 9:00 to 9:40AM | Michael Leung (USC) | Normal Approximation in Strategic Network Formation |
| 9:40 to 10:20AM | Konrad Menzel (NYU) | Many Player Asymptotics for Large Network Formation Problems |
| 10:20 to 11:00AM | Geert Ridder (USC) | Estimation of Large Network Formation Games (joint with Shuyang Sheng, UCLA) |
| 11:00 to 11:20AM | Coffee Break | |
| Session 5: Link formation with Heterogeneity | ||
| 11:20 to 12:00PM | Andreas Dzemski (Gothenburg) | An Empirical Model of Dyadic Link Formation in a Network with Unobserved Heterogeneity |
| 12:00 to 12:40PM | Ivan Fernandez-Val (BU) | Panel Quantile Effects Via Distribution Regression (joint with Victor Chernozhukov, MIT, and Martin Weidner, UCL) |
| 12:40 to 2:00PM | Lunch | |
| Session 6: High dimensional models | ||
| 2:00 to 2:40PM | Roger Moon (USC) | Estimation of High-Dimensional Graphical Models with Shape Restriction (joint with Khai Xiang Chiong, USC Dornsife INET) |
| 2:40 to 3:20PM | Martin Weidner (UCL) | Fixed-Effect Regressions on Network Data (joint with Koen Jochmans, Sciences Po) |
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Unfortunately, due to very tight physical space constraints at the venue, the dinner is by invitation only. Soi 4 is a pleasant 2.5 mile walk from campus through the Elwood and Rockridge neighborhoods. Directions can be found here. For those not wishing to walk, it is just a short Taxi/Uber ride away. ↩