Connectionists: [CFP] KDD MLG'18 - 14th International Workshop on Mining and Learning with Graphs (London, UK)

[Shobeir Fakhraei]

*14th International Workshop on Mining and Learning with Graphs (MLG
2018)August 20, 2018London, UK (co-located with KDD
2018)http://www.mlgworkshop.org/2018/ <http://www.mlgworkshop.org/2018/>
Submission Deadline:  May 8, 2018Call for papers:This workshop is a forum
for exchanging ideas and methods for mining and learning with graphs,
developing new common understandings of the problems at hand, sharing of
data sets where applicable, and leveraging existing knowledge from
different disciplines. The goal is to bring together researchers from
academia, industry, and government, to create a forum for discussing recent
advances graph analysis. In doing so, we aim to better understand the
overarching principles and the limitations of our current methods and to
inspire research on new algorithms and techniques for mining and learning
with graphs.To reflect the broad scope of work on mining and learning with
graphs, we encourage submissions that span the spectrum from theoretical
analysis to algorithms and implementation, to applications and empirical
studies. As an example, the growth of user-generated content on blogs,
microblogs, discussion forums, product reviews, etc., has given rise to a
host of new opportunities for graph mining in the analysis of social media.
We encourage submissions on theory, methods, and applications focusing on a
broad range of graph-based approaches in various domains.Topics of interest
include, but are not limited to:Theoretical aspects: - Computational or
statistical learning theory related to graphs- Theoretical analysis of
graph algorithms or models- Sampling and evaluation issues in graph
algorithms- Analysis of dynamic graphsAlgorithms and methods: - Graph
mining- Probabilistic and graphical models for structured data-
Heterogeneous/multi-model graph analysis- Network embedding models-
Statistical models of graph structure- Combinatorial graph methods-
Semi-supervised learning, active learning, transductive inference, and
transfer learning in the context of graphsApplications and analysis: -
Analysis of social media- Analysis of biological networks- Knowledge graph
construction- Large-scale analysis and modelingAll papers will be peer
reviewed, single-blinded. We welcome many kinds of papers, such as, but not
limited to: - Novel research papers- Demo papers- Work-in-progress papers-
Visionary papers (white papers)- Appraisal papers of existing methods and
tools (e.g., lessons learned)- Relevant work that has been previously
published- Work that will be presented at the main conferenceAuthors should
clearly indicate in their abstracts the kinds of submissions that the
papers belong to, to help reviewers better understand their contributions.
Submissions must be in PDF, no more than 8 pages long — shorter papers are
welcome — and formatted according to the standard double-column ACM
Proceedings Style
<http://www.acm.org/publications/proceedings-template#aL2>. The accepted
papers will be published on the workshop’s website and will not be
considered archival for resubmission purposes. Authors whose papers are
accepted to the workshop will have the opportunity to participate in a
spotlight and poster session, and some set will also be chosen for oral
presentation, and considered for $1,000 best paper award sponsored by
Kyndi.Timeline:Submission Deadline: May 8, 2018Notification: June 8, 2018
Final Version: June 28, 2018Workshop: August 20, 2018Submission
instructions can be found on http://www.mlgworkshop.org/2018/
<http://www.mlgworkshop.org/2018/> Please send enquiries to
chair at mlgworkshop.org <chair at mlgworkshop.org>We look forward to seeing you
at the workshop!Organizers:Shobeir Fakhraei (University of Southern
California, ISI)Danai Koutra (University of Michigan, Ann Arbor)Julian
McAuley (University of California, San Diego) Bryan Perozzi (Google
Research)Tim Weninger (University of Notre Dame)To receive updates about
the current and future workshops and the Graph Mining community, please
join the mailing list: https://groups.google.com/d/forum/mlg-list
<https://groups.google.com/d/forum/mlg-list>   or follow the twitter
account: https://twitter.com/mlgworkshop
<https://twitter.com/mlgworkshop> **Find
a PDF copy of the CFP here: http://www.mlgworkshop.org/2018/MLG2018_CFP.pdf
<http://www.mlgworkshop.org/2018/MLG2018_CFP.pdf> *
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