Call for Participation: Eighth Workshop on Mining and Learning with Graphs 2010 (MLG-2010)

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Call for Participation

Eighth Workshop on Mining and Learning with Graphs 2010 (MLG-2010)
http://www.cs.umd.edu/mlg2010
Washington, DC, July, 24-25
(co-located with SIG-KDD 2010 <http://www.sigkdd.org/kdd2010/>)

Key Dates
 Early registration deadline: May 15, 2010
 Regular registration deadline: June 30, 2010

Registration: http://www.kdd.org/kdd2010/registration.shtml

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This year's workshop on Mining and Learning with Graphs will be held in
conjunction with the 16th ACM SIGKDD Conference on Knowledge Discovery
and Data Mining that will take place in July 25-28, 2010 in Washington, DC.

There is a great deal of interest in analyzing data that is best
represented as a graph. Examples include the WWW, social networks,
biological networks, communication networks, and many others. The
importance of being able to effectively mine and learn from such data is
growing, as more and more structured and semi-structured data is
becoming available.  This is a problem across widely different fields
such as economics, statistics, social science, physics and computer
science, and is studied within a variety of sub-disciplines of machine
learning and data mining including graph mining, graphical models,
kernel theory, statistical relational learning, etc.

The objective of this workshop is to bring together researchers from a
variety of these areas, and discuss commonality and differences in
challenges faced, survey some of the different approaches, and provide a
forum to present and learn about some of the most cutting edge research
in this area.  As an outcome, we expect participants to walk away with a
better sense of the variety of different tools available for graph
mining and learning, and an appreciation for some of the interesting
emerging applications for mining and learning from graphs. The key
challenge we address in this workshop is how to efficiently analyze
large data sets that are relational in nature and hence easily
represented as graphs.  Such data are becoming ubiquitous in a plethora
of application and research domains and now is the time to bring
together people from these various fields to exchange ideas about how we
can mine and learn from these large data sets. The goal of this workshop
will be to explore the state-of-the-art algorithms and methods, leveraging
existing  knowledge from other sub-disciplines, to examine graph-based
models
in  the context of real-world applications, and to identify future
challenges and issues. In particular we are interested in the following
topics:

* Graph mining
* Kernel methods for structured data
* Probabilistic models for structured data
* (Multi-)relational data mining
* Methods for structured outputs
* Network analysis
* Large-scale learning and applications
* Sampling issues in graph algorithms
* Evaluation of graph algorithms
* Relationships between mining and learning with graphs and statistical
relational learning
* Relationships between mining and learning with graphs and inductive logic
programming
* Semi-supervised learning
* Active learning
* Transductive inference
* Transfer learning


We invite researchers working on mining and learning with graphs to
submit regular and position papers detailing the major points and/or
results they would present during a talk. Regular papers are a maximum
of 8 pages long in two-column format, position papers comprise 2 pages.
Authors whose papers were accepted to the workshop will have the
opportunity to give a short presentation at the workshop as well as
present their work in a poster session to promote interaction and dialog.

Please follow the submission link on the main workshop site
(http://www.cs.umd.edu/mlg2010) to submit.  We will not be doing
double-blind reviews, so please include your name and affiliation.

The workshop itself is a two-day workshop. Each day will consist of
keynote speakers, short presentations showcasing accepted papers,
discussions at end of sessions, and a poster session to promote dialog.

Important Dates

Early registration     May 15, 2010
Regular registration     June 30, 2010
Workshop                July 24-25

Organizers

*  Ulf Brefeld (Yahoo! Research, Barcelona)
*  Lise Getoor (University of Maryland)
*  Sofus A. Macskassy (Fetch Technologies / USC)

Program Committee

* Edo Arioldi
* Tanya Berger-Wolf
* Hendrik Blockeel
* Karsten Borgwardt
* Chris Burges
* Diane Cook
* Tina Eliassi-Rad
* Stephen Fienberg
* Paolo Frasconi
* Thomas Gaertner
* Brian Gallagher
* Aris Gionis
* Marko Grobelnik
* Jiawei Han
* Susanne Hoche
* Lawrence Holder
* Jure Leskovec
* George Karypis
* Samuel Kaski
* Kristian Kersting
* Dunja Mladenic
* Alessandro Moschitti
* Jennifer Neville
* Massimiliano Pontil
* Foster Provost
* Padhraic Smyth
* Swapna Somasundaran
* Eric Xing
* Philip Yu
* Mohammed Zaki
* Fabio Massimo Zanzotto
* Zhongfei (Mark) Zhang


Contact Information

Sofus A. Macskassy
Fetch Technologies
841 Apollo Street
Suite 400
El Segundo, CA 90245
http://www.cs.rutgers.edu/~sofmac
http://www-rcf.usc.edu/~macskass
sofmac@fetch.com