[robotics-worldwide] CFP: ICML 2013 Workshop on Machine Learning For System Identification

Abdeslam Boularias boularias at gmail.com
Wed Feb 27 04:27:11 PST 2013

System Identification is a fundamental problem in robotics and machine
learning offers new promising methods to solve it. The ICML Workshop
on Machine Learning For System Identification will bring together
outstanding researchers from both machine learning and robotics to
discuss this important problem from different points of view.

ICML 2013 Workshop on Machine Learning For System Identification

Call for Posters and Papers

We solicit submission of extendend abstracts or papers discussing high
quality research on all aspects of dynamical system modeling and
identification with machine learning tools. Both theoretical and
applied contributions presenting recent or ongoing research are
welcomed. The list of tools, problems, and applications includes, but
is not limited to the following:

Tools: kernel methods, regularization techniques, Bayesian estimation,
deep learning, manifold learning, spectral methods, causal inference,
active learning, reinforcement learning.

Problems: predictor estimation, state-space model identification,
impulse response modeling, non-linear system modeling, experiment

Applications: robotics, automotive, process control, motion tracking,
system biology, computational sustainability.

Submissions and Publication

An extended abstract suffices for a poster submission. Additionally,
we welcome position papers, as well as papers discussing open problems
and potential future research directions. Both extended abstracts and
position/future research papers will be reviewed by program committee
members on the basis of relevance, significance, and clarity.
Submissions should be formatted according to the ICML 2013 conference
template. The length of abstracts and papers should not exceed 8

Submission website:


Important Dates

Mar 20, 2013 - Deadline of Submission
Apr 15, 2013 - Notification of Acceptance
June 20-21, 2013 - Workshop
Francesco Dinuzzo, Abdeslam Boularias and Lennart Ljung

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