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CALL FOR PAPERS
NIPS 2013 Deep Learning Workshop
December 9th or 10th, 2013 Lake Tahoe, USA.
https://sites.google.com/site/deeplearningworkshopnips2013/
Important dates:
Submission deadline: October 9th, 2013
Acceptance notification: October 23rd, 2013
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Overview:
Deep Learning algorithms attempt to discover good representations, at
multiple levels of abstraction. There has been rapid progress in this area
in recent years, both in terms of algorithms and in terms of applications,
but many challenges remain. In this workshop, we will bring together
researchers interested in deep learning to review the recent technical
progress, discuss the challenges, and identify promising future research
directions.
The workshop invites paper submissions that will be either presented as
oral or in poster format. We encourage submissions on the following
(non-exhaustive) list of topics:
* deep learning algorithms and models (dropout, deep Boltzmann machines,
recurrent neural network, etc.)
* unsupervised feature learning models (restricted Boltzmann machines,
autoencoders, sparse coding, etc.)
* inference and optimization algorithms
* semi-supervised and transfer learning algorithms
* theoretical foundations of unsupervised / deep learning
* applications of deep learning (convolutional networks, word and sentence
representation models, etc.)
Through invited talks, a panel discussion and presentations by the
participants, this workshop will showcase the latest advances in deep learning
and address questions that are at the center of current deep learning research
(what roles do stochasticity/unsupervised learning/optimization play in deep
learning, what are the desiderata for models of images/text/speech, etc.).
Panel discussions will be led by the members of the organizing committee as
well as by prominent representatives of the machine learning, computer vision
and natural language processing communities.
Submissions:
We solicit submissions of unpublished research papers. Authors are encouraged
to restrict themselves to 8 pages (plus 1 additional page containing references
only) and must satisfy the formatting instructions of the NIPS 2013 call for
papers. Style files are available at
http://nips.cc/PaperInformation/StyleFiles.
More details on the submission process will be posted shortly. The best
papers will be awarded by an oral presentation, all other accepted papers
will have a poster presentation.
Workshop Organizers:
Yoshua Bengio (Universite de Montreal)
Hugo Larochele (Universite de Sherbrooke)
Ruslan Salakhutdinov (University of Toronto)
https://sites.google.com/site/deeplearningworkshopnips2013/
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