Saturday, June 14, 2014

CfP: TCMM 2014 International Workshop on Technical Computing for Machine Learning and Mathematical Engineering 8 - 12 September, 2014 - Leuven, Belgium

Marco Signoretto just sent me the following:

Dear Igor,
could you be so kind to post the attached CFP in Nuit Blanche?
dr. Marco Signoretto
FWO research fellow,
Katholieke Universiteit Leuven,
Kasteelpark Arenberg 10, B-3001 LEUVEN - HEVERLEE (BELGIUM)

Sure Marco, it looks like a very interesting venue:

TCMM 2014International Workshop on Technical Computing for Machine Learning and Mathematical Engineering
8 - 12 September, 2014 - Leuven, Belgium
Workshop homepage: 
The workshop will provide a venue for researchers and practitioners to interact on the latest developments in technical computing in relation to machine learning and mathematical engineering problems and methods (including also optimization, system identification, computational statistics, signal processing, data visualization, deep learning, compressed sensing and big-data). A special attention will be paid to implementations on high-level high-performance modern programming languages suitable for large-scale, parallel and distributed computing and capable to efficiently handle structured data. The emphasis is especially on the open-source alternatives, including but not limited to Julia, Python, Scala and R.
The 3 days main event (8-10 September) will consist of invited and contributed talks as well as poster presentations. It will be followed by a 2 days additional event (11-12 September) including software demos and hands-on tutorials on selected topics.
Attendees can register to the main event only or to the full workshop. Submission of extended abstracts (no longer than 2 pages) are solicited for the main event. Accepted abstracts will be presented either in the format of poster presentation or as contributed talks. Submission of demo presentations will be solicited for the two days additional event.
Topics of special interest:
  • Grid/Cloud/GPUs for technical computing
  • high-performance/parallel computing and use of related libraries (e.g., Theano)
  • efficient handling of structured data and use of related libraries (e.g., Pandas)
  • data visualization and related libraries
  • methods for exploiting sparsity in implementations
  • templates for customized solvers for (convex/distributed) optimization
  • integration of high-level languages and use of related libraries (e.g., PyCall)
  • implementation case studies:
  • performance comparison of different high-level languages for technical computing
  • application of machine learning methods on challenging problems (e.g., Kaggle challenges)
  • libraries for machine learning and mathematical engineering
Important dates:
  • Deadline extended abstract/demo submission: 31 July 2014
  • Deadline for registration: 1 September 2014
Confirmed invited speakers:
  • James Bergstra, Center for Theoretical Neuroscience, University of Waterloo
  • Jeff Bezanson, MIT
  • Luis Pedro Coelho, European Molecular Biology Laboratory (EMBL)
  • Stefan Karpinski, MIT
  • Graham Taylor, School of Engineering, University of Guelph
  • Ewout van den Berg, IBM T.J. Watson Research Center
Organizing committee:
  • Marco Signoretto, Department of Electrical Engineering, KU Leuven
  • Johan Suykens, Department of Electrical Engineering, KU Leuven
  • Vilen Jumutc , Department of Electrical Engineering, KU Leuven

For further information (including Registration, Location and Venue) see

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