Big Data meet Complex Models -- A UAI Application Workshop
Call For Papers

Date: July 15, 2013
Place: Seattle, Washington, USA
Venue: Workshop as part of the 2013 Uncertainty in Artificial
Intelligence Conference (http://auai.org/uai2013).
Abstracts Due: May 17th
Papers Due: May 24th
Author Notification: June 7th
Submission Address:
https://www.easychair.org/conferences/?conf=uaiw2013big
Registration Address: http://auai.org/uai2013 (Don't forget to
register for the workshop in addition to the main conference.)

*** The Call

As the capacity of modern computing has increased, so has the
complexity of the models explored by the UAI community: complexity
defined by many variables and many parameters which must be estimated
from data or tuned to expert opinion. The increased capacity of
modern computing has also made it easier and easier to collect
fine-grained data from a wide variety of subject interactions with
various computer systems. This is often called "Big Data" because the
data sets can become very large. But the true difficulty often lies
with the nature of the data, and not just the size. Big Data don't
look like the carefully planned and cleaned data sets from
experimental or observational studies. Instead, they are
heterogeneous: encompassing a wide variety of types, quality and
completeness. Because Big Data are often gathered in an opportunistic
fashion, issues of missing responses and selection bias are often not
ignorable.

The focus this year is on the intersection of the complex models
studied by the UAI community with the emerging challenges of Big
Data. In particular, we invite papers on the following themes:

* Data preparation and cleaning
* Robustness, resistance (to errors in the data) and treatment of outliers
* Transforming data for further processing
* Prepossessing of data and use of the output of one model as the input
to another (for example, using the output of natural language tools
as the input to a Bayesian network)
* Data fusion: combining data of multiple types
* Treatment of missing data and selection bias
* Combining data and expert opinion
* Dealing with problems in estimating model parameters from incomplete
data, or models that are not identifiable from the data


This list is meant to be suggestive and not exhaustive; other papers
with an application focus are welcome. Also welcome are papers which
represent works in progress or which explore a practical problem or
issue without a final resolution. Workshop papers will be selected
with the goal of stimulating discussion of critical issues within the
community of practice.

*** Instructions for Authors

Submissions will be peer reviewed and papers will be published
online. Authors who wish to withhold their paper from publication
(either because it contains references to proprietary data, or because
they wish to publish it later at a different venue) can request that
only the abstract be published. Papers should follow the general UAI
conference guidelines as to format and length, although these will be
more loosely enforced.

Abstracts should be submitted
to https://www.easychair.org/conferences/?conf=uaiw2013big
by May 17, 2013, with full papers due on May 24, 2013.
Author notifications are expected around June 7, 2013. For
questions contact the chair at mailto:uaiw2013big@easychair.org.

There are several collocated workshops. Papers may only be
submitted to one of them. If the program committee feels that a
paper would be a better fit in a different workshop, with the
authors will pass the paper along to the other workshop's
committee.

*** Conference Details

This workshop is offered as part of the 29th
Uncertainty in Artificial Intelligence conference (UAI 2013,
http://auai.org/uai2013), July 11-15th in Seattle, WA. It will be
collocated with other UAI workshops on the last day of the conference,
July 15th. Registration is handled through the main conference web
site, which also gives information about lodging and travel. One
registration fee covers all of the workshops: people who register for
this workshop may split their time between all the workshops.


*** Program Committee:

Chair: Russell Almond, Florida State University
Co-chair: Thomas O'Neill, The American Board of Family Medicine

Marek J Druzdzel, University of Pittsburgh and Bialystok University of
Technology, Poland
Julia Flores, Universidad de Castilla-La Mancha, Spain
Linda van der Gaag, Utrecht University, The Netherlands
Lionel Jouffe, Bayesia SAS
Kathryn Laskey, George Mason University
Suzanne Mahoney, Innovative Decisions, Inc.