The following workshop will take place this August in Washington, D.C. I
encourage anyone interested in the challenges associated with using
machine learning and data analysis methods in conjunction with space
missions to contribute and participate.
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Call for Papers and Participation: ICML-2003 Workshop
Machine Learning Technologies for Autonomous Space Applications
Thursday, August 21, 2003, Washington, D.C.
http://www.lunabots.com/icml2003/
Submission deadline: May 1, 2003
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The ICML 2003 workshop on Machine Learning Technologies for Autonomous
Space Applications invites contributions from researchers and
practitioners in machine learning, space science, and mission
planning. This workshop aims to bring together those interested in
developing novel machine learning algorithms for autonomous spacecraft
with those concerned with misson safety, performance, and engineering
constraints to bridge the "applicability divide". Despite progress in
developing applicable ML techniques, adoption and integration into
fielded remote space missions remains a challenge. The workshop will
provide a context for mission engineers and scientists to present
their "wish lists" and real-world constraints to machine learning
researchers and for ML scientists to present pertinent, cutting-edge
technologies. The ultimate goal is to foster research and development
leading to the application of machine learning methods on real, flown
spacecraft.
We convene this workshop as a forum where we can address critical
questions such as:
* How can we design algorithms that can train for a long time under
controlled situations, but must work almost perfectly in a remote,
autonomous setting?
* How can ML techniques be tested so as to convince someone outside
the field that they are reliable, robust, and effective for real
space systems? What are the best analogue problems and situations,
here on Earth, for the development and study of applicable ML
techniques?
* Are there specific, possibly novel, metrics and methodologies for
evaluation that would be most appropriate for these problems?
* What ML algorithms drawn from other domains (e.g., tasks with a high
cost of failure) are applicable to the problems faced by fielded
space missions?
* Can we provide formal performance guarantees for ML algorithms in
the constrained and sometimes hostile environments in which remote
space systems will exist?
* How can we strengthen connections between ML researchers and the
people making operational decisions for space missions?
For a full description of the workshop focus and goals, visit the
website at http://www.lunabots.com/icml2003/ .
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Format
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This will be a one-day workshop. The day will open with a keynote
presentation by Dr. Steve Chien of JPL, a renowned expert in automated
planning and scheduling for space exploration. In addition, the
program will feature a mix of technical presentations by machine
learning and space mission scientists, ample discussion sessions, and
a small-group brainstorming exercise built around exemplar practical
scenarios.
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Paper Submissions
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We welcome contributions of innovative, controversial, yet well
reasoned ideas. Papers, 3-5 pages in length, may be submitted on one
of three topics: technical challenges/solutions, social
challenges/solutions, or opportunities for the use of ML in space
missions. In addition, interested participants who do not wish to
submit a technical paper may submit a one-page statement of interests
and potential contributions to the workshop.
For more details, including paper format and submission address, see:
http://www.lunabots.com/icml2003/CFP.html#sub
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Important Dates
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May 1, 2003: Technical submissions due
May 25, 2003: Notification of acceptance
June 6, 2003: Camera ready copies of both bios and technical submissions
August 1, 2003: Attendance-only submissions due
Note that biographies submitted in this category after the June 6
camera-ready date may not appear in the proceedings, though we will
attempt to make them available on the workshop web site.
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Program Committee
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Kiri Wagstaff (JHU/APL) - Co-chair
Amy McGovern (University of Massachusetts Amherst) - Co-chair
Terran Lane (University of New Mexico) - Co-chair
Jim Bell (Cornell University)
Steve Chien (NASA/JPL)
Dennis DeCoste (NASA/JPL)
Manfred Huber (University of Texas at Arlington)
Ted Roush (NASA/Ames)
Donna Shirley (University of Oklahoma)
Tim Stough (NASA/JPL)
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