Connectionists: CFP: ICML Workshop on Structured Learning: Inferring Graphs from Structured and Unstructured Inputs (SLG2013)

[Lise Getoor]

Structured Learning: Inferring Graphs from Structured and Unstructured
Inputs (SLG2013)
ICML workshop,  June 16, 2013 (day between ICML & NAACL)
https://sites.google.com/site/slgworkshop2013/
Submission Deadline: April 15, 2013


OVERVIEW

Structured learning involves learning and making inferences from inputs
that can be both unstructured (e.g., text) and structured (e.g., graphs and
graph fragments), and making predictions about outputs that are also
structured as graphs.   Examples include the construction of knowledge
bases from noisy extraction data, inferring temporal event graphs from
newswire or social media, and inferring influence structure on social
graphs from multiple sources.

One of the challenges of this setting is that it often does not fit into
the classic supervised or unsupervised learning paradigm.   In essence, we
have one large (potentially infinite) partially observed input graph, and
we are trying to make inferences about the unknown aspects of this graph's
structure.   Often times there is side information available, which can be
used for enrichment, but in order to use this information, we need to infer
mappings for schema and ontologies that describe that side information,
perform alignment and entity resolution, and reason about the added utility
of the additional sources.  The topic is extremely pressing, as many of the
modern challenges in extracting usable knowledge from (big) data fall into
this setting.  Our focus in this workshop is on the machine learning and
inference methods that are useful in such settings.

Topics of interest include, but are not limited to:

- Graph-based methods for entity resolutions and word sense disambiguation
- Graph-based representations for ontology learning
- Graph-based strategies for semantic relations identification
- Making use of taxonomies and encoding semantic distances in graphs
- Random walk methods in graphs
- Spectral graph clustering and multi-relational clustering
- Semi-supervised graph-based methods
- Graph summarization

Our goal is to bring together researchers in graphical models, structured
prediction, latent variable relational models and statistical relational
learning in order to (a) exchange experiences applying various methods to
these graph learning domains, (b) share their successes, and (c) identify
common challenges.  The outcomes we expect are (1) a better understanding
of the different existing methods across disparate communities, (2) an
identification of common challenges, and (3) a venue for sharing resources,
tools and datasets.

The workshop will consist of a number of invited talks in each of these
areas, a poster session where participants can present their work, and
discussion.

SUBMISSION INFORMATION

We solicit short, poster-length submissions of up to 2 pages. All accepted
submissions will be presented as posters, and a subset of them may be
considered for oral presentation. Submissions reporting work in progress
are acceptable, as we aim for the workshop to offer a venue for stimulating
discussions.

Submissions must be in PDF format, and should be made through Easychair at
https://www.easychair.org/conferences/?conf=slg-2013
Important dates

- Submission deadline: April 15, 2013
- Notification of acceptance: April 30, 2013
- Final versions of accepted submissions due: May 15, 2013
- Workshop date: Sunday, June 16, 2013
(Note: Most of the ICML workshops are taking place AFTER the conference,
while this workshop takes place before the main conference, on the same day
as ICML tutorials, in order to make it easier for participants from NAACL
HLT conference to attend).

ORGANIZING COMMITTEE

- Hal Daume III, University of Maryland
- Evgeniy Gabrilovich, Google
- Lise Getoor, University of Maryland
- Kevin Murphy, Google

PROGRAM COMMITTEE(confirmed to date)

- Jeff Dalton, UMass
- Laura Dietz, UMass
- Thorsten Joachims, Cornell
- Daniel Lowd, University of Oregon
- Mausam, University of Washington
- Jennifer Neville, Purdue University
- Stuart Russell, UC Berkeley
- Ivan Titov, Saarland University
- Daisy Zhe Wang, University of Florida
- Jerry Zhu, University of Wisconsin - Madison

FURTHER INFORMATION

For further information, please contact the workshop organizers at
slg-2013-chairs at googlegroups.com
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