Marco just sent me the following:
Dear Igor, could you be so kind to post the attached CFP (last call for contributions - TCMM 2014) on Nuit Blanche? kind regards Marco -- dr. Marco Signoretto FWO research fellow, ESAT - STADIUS, Katholieke Universiteit Leuven, Kasteelpark Arenberg 10, B-3001 LEUVEN - HEVERLEE (BELGIUM) Homepage: http://homes.esat.kuleuven.be/ ~msignore/
Last Call for Contributions - TCMM 2014 International Workshop on Technical Computing for Machine Learning and Mathematical Engineering 8 - 12 September, 2014 - Leuven, Belgium Workshop homepage: http://www.esat.kuleuven.be/stadius/tcmm2014/ 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). The emphasis is especially on open-source implementations in high-level programming languages, including but not limited to Julia, Python, Scala and R. For further information see the workshop homepage. 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 are solicited for the main event. Submission of demo presentations are solicited for the two days additional event. For further information (including Registration, Location and Venue) see details at the workshop website. Important dates: Deadline extended abstract/demo submission: 31 July 2014 Deadline for registration: 1 September 2014 Confirmed invited speakers (talks and tutorials): James Bergstra, Center for Theoretical Neuroscience, University of Waterloo: Theano and Hyperopt: Modelling, Training, and Hyperparameter Optimization in Python Jeff Bezanson, MIT: TBA Luis Pedro Coelho, European Molecular Biology Laboratory (EMBL): Large Scale Analysis of Bioimages Using Python Steven Diamond, Stanford University Convex Optimization in Python with CVXPY Stefan Karpinski, MIT TBA Graham Taylor, School of Engineering, University of Guelph: An Overview of Deep Learning and Its Challenges for Technical Computing Ewout van den Berg, IBM T.J. Watson Research Center: Tools and Techniques for Sparse Optimization and Beyond 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 http://www.esat.kuleuven.be/stadius/tcmm2014/
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