Distributed machine learning and sparse representation with massive data sets
Distributed machine learning and sparse representation with massive data sets (DMMD 2011)ScopeThe exponentially increasing demand for computing power as well as physical and economic limitations has contributed to a proliferation of distributed and parallel computer architectures. To make better use of current and future high-performance computing, and to fully benefit from these massive amounts of data, we must discover, understand and exploit the available parallelism in machine learning. Simultaneously, we have to model data in an adequate manner while keeping the models as simple as possible, by making use of a sparse representation of the data or sparse modelling of the respective underlying problem. |
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Who Should Attend
- Researchers in machine learning and statistics
- Scientists from areas producing massive data sets, e.g. astronomy, energy, sensor networks
- Parallel computing experts and practitioners
- Curators of massive datasets or learning problems
Registration
Registration required. Attendance is free but limited to approx. 50 participants (first in, best dressed).
To register, simply send an email to
Oliver.Obst@csiro.auContact Information
Dr Oliver ObstICT Centre
E-mail: Oliver.Obst@csiro.au
Telephone: +61 2 9372 4710
Fax: +61 2 9372 4161
Program
The program is now available as a PDF.Call for Papers / Extended Abstracts
Through a combination of invited talks, contributed presentations, discussions and posters, we hope to gain a better understanding of available algorithms and best practices, as well as their inherent limitations.
Accepted submissions will be presented either as contributed talks or during the workshop poster discussion period. Submission should be extended abstracts, at most four pages long, in NIPS format (see instructions below).
Suggested topics include, but are not limited to:
- Distributed, Multicore and Cluster based Learning Techniques
- Machine Learning on Alternative Hardware (GPUs, Robots, Sensor Networks, Mobile Phones, Cell Processors ...)
- Sparsity in Machine Learning and Statistics
- Learning results and techniques on Massive Datasets
- Dimensionality Reduction, Sparse Matrix, Large Scale Kernel Methods
- Fast Online Algorithms for Large Scale Data
- Parallel Computing Tools and Libraries
Invited Speakers
- Samy Bengio (Google Research, CA, USA)
- Barbara Hammer (University of Bielefeld, Germany)
- Yann LeCun (New York University, NY, USA)
- Michael Mahoney (Stanford University, CA, USA)
Important Dates
- Submission deadline: 1 November, 2010
- Registration deadline: 31 December, 2010
- Symposium: 18-20 January, 2011
Funded by a CSIRO OCE Science Team Cutting Edge Science Symposium grant.
Organising chair: Oliver Obst.
Venue: Marsfield Lecture Theatre, Sydney.
Submission instructions
Submissions should be short papers / extended abstracts of at most 4 pages in length in NIPS format (please download a local copy of the NIPS 2010 template, or go to http://nips.cc/PaperInformation/StyleFiles), and should include the title, authors' names, postal and email addresses, and an abstract not to exceed 150 words. Submissions in pdf format only should be sent to Oliver Obst with the subject line "DMMD 2011 Submission" and with the title, authors' names and abstract included in the body of the message.
Submissions will be reviewed by the program committee and selected submissions may be accepted either as a contributed talk or as a poster presentation. Please note submission of extended abstracts to DMMD 2011 does not preclude authors from submitting full versions of their work to conference or journal.
Please note that one author of each accepted paper must present the paper at DMMD 2011.
If quality of submissions permits, a selection of contributions will be considered for a special issue / collected volume. Prospective authors will be notified, and a separate call for papers will be issued in this case.
Program Committee
- Samy Bengio (Google Research, CA, USA)
- Joschka Boedecker (Osaka University, Japan)
- Stephan Chalup (University of Newcastle, Newcastle)
- Tim Cornwell (CSIRO CASS, Sydney)
- Ying Guo (CSIRO ICT Centre, Sydney)
- Barbara Hammer (University of Bielefeld, Germany)
- Yann LeCun (New York University, NY, USA)
- Simon Lucey (CSIRO ICT Centre, Sydney)
- Michael Mahoney (Stanford University, CA, USA)
- N. Michael Mayer (National Chung Cheng University, Taiwan)
- Mikhail Prokopenko (CSIRO ICT Centre, Sydney)
- Scott Sanner (NICTA & ANU, Canberra)
- John A. Taylor (CSIRO CMIS, Canberra)
- Rosalind Wang (CSIRO ICT Centre, Sydney)
- TBA
