Overview

This workshop aims to bring together a diverse and cross-disciplinary set of researchers to discuss recent advances and future directions for developing new network methods in statistics and machine learning. In particular, we are interested in

network methods that learn the patterns of interaction, flow of information, or propagation of effects in social and information systems,
empirical studies, particularly attempts to bridge observational methods and causal inference, and studies that combine learning, networks, and computational social science,
research that unifies the study of both structure and content in rich network datasets.
While this research field is broad and diverse, there are emerging signs of convergence. For example, in the study of information diffusion, social media and social network researchers are beginning to use rigorous tools to distinguish effects driven by social influence, homophily, or external processes -- subjects historically of intense interest amongst statisticians and social scientists. Similarly, there is a growing statistics literature developing learning approaches to study topics popularized earlier within the physics community, including clustering in graphs, network evolution, and random-graph models. Finally, learning methods are increasingly used in highly complex application domains, such as large-scale knowledge graph construction and use, and massive social networks like Facebook and LinkedIn. These applications are stimulating new scientific and practical questions that often cut across disciplinary boundaries.

Workshop format

This is a one-day workshop. The program will feature 4 invited talks, poster spotlights and a poster session, and a panel discussion. For up-to-date information on the workshop, please check http://tinyurl.com/NetworksNIPS2015.

Online Submissions

We welcome the following types of papers:

Research papers that introduce new models or apply established models to novel domains,
Research papers that explore theoretical and computational issues, or
Position papers that discuss shortcomings and desiderata of current approaches, or propose new directions for future research.

Submissions will be lightly peer-reviewed. We encourage authors to emphasize the role of learning and its relevance to the application domains at hand. In addition, we hope to identify current successes in the area, and will therefore consider papers that apply previously proposed models to novel domains and data sets.

Submission format

Submissions should be 4-to-8 pages long, and adhere to NIPS format (http://nips.cc/PaperInformation/StyleFiles). Please make the author information visible as in the final draft.

Submission procedure

Please email your submissions to https://easychair.org/conferences/?conf=nipsnetworks2015

Important dates

Deadline for Submissions: Monday, November 2, 2015
Notification of Decision: Thursday, November 5, 2015

The workshop is endorsed by the ISBA. The organizers have been invited to nominate graduate students or junior researchers (up to five years after graduation) who will be presenting at the workshop for ISBA Travel Awards. Two such awards will be granted (across all NIPS workshops endorsed by the ISBA), offering up to 700 USD in support. To be considered for an ISBA Travel Award, submissions must be submitted early, by October 12, 2015.

Organizers:

Edo Airoldi, Harvard University
David Choi, Carnegie Mellon University
Aaron Clauset, University of Colorado, Boulder
Panos Toulis, Harvard University
Johan Ugander, Stanford University

Previous NIPS workshops:

NIPS 2014: Networks: From Graphs to Rich Data
NIPS 2013: Frontiers of Network Analysis: Methods, Models, and Applications
NIPS 2012: Social Network and Social Media Analysis: Methods, Models and Applications
NIPS 2010: Networks Across Disciplines: Theory and Applications
NIPS 2009: Analyzing Networks and Learning with Graphs

Contact

You can reach the organizers at NIPSnetworks@gmail.com