Connectionists: (Deadline extended) CFP - ECML/PKDD Workshop: Tensor Methods for Machine Learning

[Maximilian Nickel]

[Apologies for multiple postings]

Please redistribute:

ECML/PKDD Workshop: Tensor Methods for Machine Learning
Date: Friday, September 27th, 2013
Location: Prague, Czech Republic
Website: http://www.cip.ifi.lmu.de/~nickel/tml2013/

*** EXTENDED DEADLINE: July 5th, 2013! ***

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Call for Papers
----------------------
Tensors, as generalizations of vectors and matrices, have become
increasingly popular in different areas of machine learning and data
mining, where they are employed to approach a diverse number of difficult
learning and analysis tasks. Prominent examples include learning on
multi-relational data and large-scale knowledge bases, recommendation
systems, computer vision, mining boolean data, signal processing,
neuroimaging or the analysis of time-varying networks. The success of
tensors methods is strongly related to their ability to efficiently model,
analyze and predict data with multiple modalities. To address specific
challenges and problems, a variety of methods has been developed in
different fields of application. This workshop should serve as a basis for
an interdisciplinary exchange of methods, ideas and techniques, with the
goal to develop a deeper understanding of tensor methods for machine
learning, further advance existing approaches and enable new approaches to
important problems. A particular focus of this workshop is to uncover
underlying principles in tensor methods, their applications, and associated
problems. The workshop is intended for researchers in the machine learning,
data mining, and tensor communities to discuss novel methods and
applications as well as theoretical advances.

Topics of interest include, but are not limited to
  • Statistical analysis and learning theory related to tensor methods,
factorizations or analysis.
  • Novel techniques and methods for tensor factorization or tensor
completion.
  • New factorization models, loss functions or regularization methods.
  • Probabilistic/Bayesian approaches to tensor factorizations.
  • Tensor methods for large-scale and distributed problems.
  • Novel applications of tensor methods in machine learning and
statistics.
  • Empirical studies that provide new insight into tensor methods for
machine learning.
  • Related techniques and methods in machine learning such as matrix
factorizations.

More information about the workshop is available from the workshop's
website at:
http://www.cip.ifi.lmu.de/~nickel/tml2013/


Submission Instructions
------------------------------------
Submitted papers should be at most 4 (extended abstract) or 8 (full paper)
pages long and formatted according to the Springer LNAI guidelines.

All submitted papers will be subject to peer review. Accepted papers will
be presented as a talk or poster at the workshop and will also be published
on the workshop's website.

For manuscript submission, please use the EasyChair site at:
https://www.easychair.org/conferences/?conf=tml2013


Important Dates
------------------------
For manuscript submission, please consider the following deadlines
  • Paper Submission: Friday, July 5th, 2013 (EXTENDED!)
  • Acceptance Notification: Friday, July 19th, 2013
  • Camera-Ready Paper Submission: Friday, August 2nd, 2013


Program Chairs
-----------------------
• Maximilian Nickel, Ludwig Maximilian University Munich, Germany
• Volker Tresp, Siemens AG, Germany


Program Committee
----------------------------------------------------------
• Alwin Stegeman, University of Groningen, Netherlands
• Evrim Acar Ataman, University of Copenhagen, Denmark
• Franz Király, TU Berlin, Germany
• Jaakko Hollmén, Aalto University, Finland
• Morten Mørup, Technical University of Denmark, Denmark
• Pauli Miettinen, Max-Planck Institut für Informatik, Germany
• Rainer Gemulla, Max-Planck Institut für Informatik, Germany
• Ryota Tomioka, University of Tokyo, Japan
• Shipeng Yu, Siemens Medical Solutions USA, USA
• Steffen Rendle, Universität Konstanz, Germany
• Taylan Cemgil, Bogazici University Istanbul, Turkey
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