[Infovis] Submission Deadline Extended: Call for Participation for IEEE VIS 2018 Workshop on Machine Learning from User Interaction for Visualization and Analytics

John Wenskovitch johnwenskovitch at gmail.com
Wed Jun 27 12:57:14 CEST 2018


Please note below that the paper submission deadline has been extended
until July 15.


*IEEE VIS 2018 Workshop:*
*MACHINE LEARNING FROM USER INTERACTION FOR VISUALIZATION AND ANALYTICS*

*CALL FOR PAPERS*

*Date and Location*: October 21 or 22, 2018 in Berlin, Germany

*Website*: https://learningfromusersworkshop.github.io/

The goal of this workshop is to bring together researchers from across the
VIS community – SciVis, InfoVis, and VAST – to share their knowledge and
build collaborations at the intersection of the Machine Learning and
Visualization fields, with a focus on learning from user interaction. Our
intention in this workshop is to pull expertise from across all fields of
VIS in order to generate open discussion about how we currently learn from
user interaction and where we can go with future research in this area. We
hope to foster discussion regarding systems, interaction models, and
interaction techniques across fields within the VIS community, rather than
the current state of having these discussions independently contained
within the SciVis/InfoVis/VAST fields. Further, we hope to collaboratively
create a research agenda that explores the future of machine learning with
user interaction based on the discussion during the workshop.

*WORKSHOP TOPICS*

The topic of the workshop will focus on issues and opportunities related to
the use of machine learning to learn from user interaction in the course of
data visualization and analysis. Specifically, we will focus on research
questions including:

   - How are machine learning algorithms currently learning from user
   interaction, and what other possibilities exist?
   - What kinds of interactions can provide feedback to machine learning
   algorithms?
   - What can machine learning algorithms learn from interactions?
   - Which machine learning algorithms are most applicable in this domain?
   - How can machine learning algorithms be designed to enable user
   interaction and feedback?
   - How can visualizations and interactions be designed to exploit machine
   learning algorithms?
   - How can visualization system architectures be designed to support
   machine learning?
   - How should we manage conflicts between the user’s intent and the data
   or machine learning algorithm capabilities?
   - How can we evaluate systems that incorporate both machine learning
   algorithms and user interaction together?
   - How can machine learning and user interaction together make both
   computation and user cognition more efficient?
   - How can we support the sensemaking process by learning from user
   interaction?


*SUBMISSIONS*

We have two submission tracks: for papers and for posters.

*Papers*

We invite research and position papers between 5 and 10 pages in length
(NOT including references). All submissions must be formatted according to
the VGTC conference style template
<http://junctionpublishing.org/vgtc/Tasks/camera.html> (i.e., NOT the
journal style template that full papers use). Papers are to be submitted
online through the Precision Conference System
<https://new.precisionconference.com/user/login?society=vgtc> *at the
Machine Learning from User Interaction for Visualization and Analytics
track*. All papers accepted for presentation at the workshop will be
published on IEEE Xplore and linked from the workshop website. All papers
should contain full author names and affiliations. If applicable, a link to
a short video (up to 5 min. in length) may also be submitted. The papers
will be juried by the organizers and selected external reviewers and will
be chosen according to relevance, quality, and likelihood that they will
stimulate and contribute to the discussion. At least one author of each
accepted paper needs to register for the conference (even if only for the
workshop). Registration information will be available on the IEEE VIS
website <http://ieeevis.org/year/2018/welcome>.

Important Dates

   - Submission deadline:  June 30, 2018   July 15, 2018
   - Author notification:   July 31, 2018   August 6, 2018
   - Camera-ready deadline: August 20, 2018
   - Speaker Schedule Available: September 15, 2018
   - Workshop: October 21 or 22, 2018


*Posters*

We invite both late-breaking work and contributions in this area from other
research domains to submit extended abstracts between 2 and 4 pages in
length (NOT including references). All submissions must be formatted
according to the VGTC conference style template
<http://junctionpublishing.org/vgtc/Tasks/camera.html> (i.e., *NOT the
journal style template that full papers use*). Extended abstracts are to be
submitted online through the Precision Conference System (additional
details TBA; do NOT use the PCS link above to submit extended abstracts for
posters). All abstracts accepted for presentation at the workshop will be
published on IEEE Xplore and linked from the workshop website. All
abstracts should contain full author names and affiliations. If applicable,
a link to a short video (up to 5 min. in length) may also be submitted. The
abstracts will be juried by the organizers and selected external reviewers
and will be chosen according to relevance, quality, and likelihood that
they will stimulate and contribute to the discussion. At least one author
of each accepted poster needs to register for the conference (even if only
for the workshop). Registration information will be available on the IEEE
VIS website <http://ieeevis.org/year/2018/welcome>.

Important Dates

   - Submission deadline: August 15, 2018
   - Author notification: September 1, 2018
   - Camera-ready deadline: October 1, 2018
   - Workshop: October 21 or 22, 2018


*ORGANIZERS*

   - John Wenskovitch, Virginia Tech (jw87 at vt.edu)
   - Michelle Dowling, Virginia Tech (dowlingm at vt.edu)
   - Chris North, Virginia Tech
   - Remco Chang, Tufts University
   - Alex Endert, Georgia Tech
   - David Rogers, Los Alamos National Lab


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