Connectionists: CFP: AAAI 2013 SPRING SYMPOSIUM ON LIFELONG MACHINE LEARNING

[Honglak Lee]

CALL FOR PAPERS
AAAI 2013 SPRING SYMPOSIUM ON LIFELONG MACHINE LEARNING

Submissions due:  Oct 5, 2012


OVERVIEW

Humans learn to solve increasingly complex tasks by continually
building upon and refining knowledge over a lifetime of experience.
This process of continual learning and transfer allows us to rapidly
learn new tasks, often with very little training. Over time, it
enables us to develop a wide variety of complex abilities across many
domains.

Despite recent advances in transfer learning and representation
discovery, lifelong machine learning remains a largely unsolved
problem. Lifelong machine learning has the huge potential to enable
versatile systems that are capable of learning a large variety of
tasks and rapidly acquiring new abilities. These systems would benefit
numerous applications, such as medical diagnosis, virtual personal
assistants, autonomous robots, visual scene understanding, language
translation, and many others.

Learning over a lifetime of experience involves a number of procedures
that must be performed continually, including:
1.) Discovering representations from raw sensory data that capture
higher-level abstractions,
2.) Transferring knowledge learned on previous tasks to improve
learning on the current task,
3.) Maintaining the repository of accumulated knowledge, and
4.) Incorporating external guidance and feedback from humans or other agents.

Each of these procedures encompasses one or more subfields of machine
learning and artificial intelligence. The primary goal of this
symposium is to bring together practitioners in each of these areas
and focus discussion on combining these lines of research toward
lifelong machine learning.



TOPICS

The symposium will include paper presentations, talks, and discussions
on a variety of topics related to lifelong learning, including but not
limited to:

knowledge transfer
- active transfer learning
- multi-task learning
- cross-domain transfer
- knowledge/schema mapping
- source knowledge selection
- one-shot learning
- transfer over long sequences of tasks

continual learning
- online multi-task learning
- online representation learning
- knowledge maintenance/revision
- developmental learning
- scalable transfer learning
- task/concept drift
- self-selection of tasks

representation discovery
- learning from raw sensory data
- deep learning
- latent representations
- multi-modal/multi-view learning
- multi-scale representations

incorporating guidance from external teachers
- learning from demonstration
- skill shaping
- curriculum-based training
- interactive learning
- corrective feedback
- agent-teacher communication

frameworks for lifelong learning
- architectures
- software frameworks
- testbeds
- evaluation methodology

applications of lifelong learning
- data sets
- application domains/environments
- simulators
- deployed applications

Within these topics, the symposium will explore lifelong learning in
different problem formats, including classification, regression, and
sequential decision-making problems.



SUBMISSION INSTRUCTIONS

Prospective participants are invited to submit either full-length
papers (up to 6 pages) or short papers/extended abstracts (2 pages) in
PDF format using the EasyChair conference system:
https://www.easychair.org/conferences/?conf=aaaisss13lml.

All submissions should follow AAAI style guidelines. While we
encourage original work, we will also consider modified versions or
extended abstracts of previously published work, provided it is
directly related to the symposium goals and the prior publication is
explicitly identified.



IMPORTANT DATES

October 5, 2012 - Submissions due via EasyChair
November 2, 2012 - Notification of acceptance/rejection sent to authors
January 18, 2013 - Final papers and signed distribution license due to AAAI
February 15, 2013 - Invited participants registration deadline
March 8, 2013 - Final (open) registration deadline
March 25-27, 2013 - Symposium at Stanford University, California



ORGANIZING COMMITTEE

Chair:
Eric Eaton (Bryn Mawr College)

Committee Members:
Terran Lane (Google)
Honglak Lee (University of Michigan)
Michael Littman (Brown University)
Fei Sha (University of Southern California)
Thomas Walsh (University of Kansas)



FOR MORE INFORMATION

Symposium website:  http://cs.brynmawr.edu/~eeaton/AAAI-SSS13-LML/