Program
Main Event
Monday September 8
| 13.00 - 14.00 | Registration and welcome coffee Salons Arenberg castle |
| 14.00 - 14.10 | Welcome by Marco Signoretto Auditorium Arenberg Castle |
| 14.10 - 15.40 | Tools and Techniques for Sparse Optimization and Beyond Ewout van den Berg, IBM T.J. Watson Research Center Auditorium Arenberg Castle |
| 15.40 - 16.10 | Coffee break Salons Arenberg Castle |
| 16.10 - 17.00 | Oral Session 1 (2x25min) Technical Computing: Optimization Auditorium Arenberg Castle |
| 17.00 - 19.00 | Reception Salons Arenberg Castle |
Tuesday September 9
| 09.00 - 10.30 | Julia: A Fresh Approach to Technical Computing Stefan Karpinski, MIT Auditorium Arenberg Castle |
| 10.30 - 11.00 | Coffee break Salons Arenberg castle |
| 11.00 - 12.30 | Large Scale Analysis of Bioimages Using Python Luis Pedro Coelho, European Molecular Biology Laboratory (EMBL) Auditorium Arenberg Castle |
| 12.30 - 12.45 | Poster Spotlights Auditorium Arenberg Castle |
| 12.45 - 14.00 | Lunch in Alma 3 |
| 14.00 - 15.30 | Poster Session Rooms S 00.04 and S 00.05 |
| 15.30 - 16.00 | Coffee break Salons Arenberg Castle |
| 16.00 - 17.15 | Oral Session 2 (3x25min) Technical Computing: Learning and Visualizing Relations from Data Auditorium Arenberg Castle |
| 17.15 - 18.15 | Exotic Numeric Types in Julia for Fun and
Profit Stefan Karpinski, MIT Auditorium Arenberg Castle |
| 19.00 | Dinner in Faculty Club |
Wednesday September 10
| 09.00 - 10.30 | An Overview of Deep Learning and Its Challenges for Technical Computing Graham Taylor, School of Engineering, University of Guelph Auditorium Arenberg Castle |
| 10.30 - 11.00 | Coffee Break Salons Arenberg Castle |
| 11.00 - 12.30 | Theano: a Fast Python Library for Modelling and Training Pascal Lamblin, UdeM Auditorium Arenberg Castle |
| 12.30 - 14.00 | Lunch in Alma 3 |
Tutorials
(Attendees will be endowed with laptops to follow the hands-on tutorials)
Thursday September 11
| 09.30 - 11.00 | Getting Started with Julia Stefan Karpinski, MIT Room S 00.03 |
| 11.00 - 11.30 | Coffee Break Hall Rooms S |
| 11.30 - 12.30 | Getting Started with Julia, Part II Jeff Bezanson, MIT Room S 00.03 |
| 12.30 - 14.00 | Lunch in Alma 3 |
| 14.00 - 15.00 | Pylearn2: Using Theano for Deep Learning Pascal Lamblin, UdeM Room S 00.03 |
| 15.00 - 15.30 | Coffee break Hall Rooms S |
| 15.30 - 16.30 | Pylearn2: Using Theano for Deep Learning, Part II Pascal Lamblin, UdeM Room S 00.03 |
| 16:30 - 17:00 | Demo Spotlights Room S 00.03 |
| 17.00 - 18.30 | Demo Session Rooms S 00.04 and S 00.05 |
| 19.00 | Dinner in Voltaire |
Friday September 12
| 09.30 - 11.00 | Convex Optimization in Python with CVXPY, Part I Steven Diamond, Eric Chu and Stephen Boyd, Stanford University Room S 00.03 |
| 11.00 - 11.30 | Coffee Break Hall Rooms S |
| 11.30 - 12.30 | Convex Optimization in Python with CVXPY, Part II Steven Diamond, Eric Chu and Stephen Boyd, Stanford University Room S 00.03 |
| 12.30 - 14.00 | Lunch in Alma 3 |
| 14.00 - 15.30 | Computing in Parallel With Python and Visualizing the Results, Part I Luis Pedro Coelho, European Molecular Biology Laboratory (EMBL) Room S 00.03 |
| 15.30 - 16.00 | Coffee Break Hall Rooms S |
| 16.00 - 17.00 | Computing in Parallel With Python and Visualizing the Results, Part II Luis Pedro Coelho, European Molecular Biology Laboratory (EMBL) Room S 00.03 |
Oral Session 1
Monday September 8, 16.10 - 17.00Auditorium Arenberg Castle
Technical Computing: Optimization
- High Level High Performance Computing for Multitask Learning
Marco Signoretto, Emanuele Frandi, Zahra Karevan and Johan A. K. Suykens, KU Leuven - An overview of IBM ILOG CPLEX MIP Solver
Andrea Tramontani and Pierre Bonami, CPLEX Optimization, IBM
Oral Session 2
Tuesday September 9, 16.00 - 17.15Auditorium Arenberg Castle
Technical Computing: Learning and Visualizing Relations from Data
- Topological Data Analysis: Heuristics and Lessons Learned
Toni Verbeiren and Jan Aerts, KU Leuven - GPU-accelerated Metric Learning from Multiple Relations
Bence Bolgár and Péter Antal, Budapest University of Technology and Economics - Hyperparameter Tuning in Python Using Optunity
Marc Claesen, Jaak Simm, Dusan Popovic and Bart De Moor, KU Leuven
Poster Session
Tuesday September 9, 14.00 - 15.30Rooms S 00.04 and S 00.05
(poster should be prepared in A0 portrait format)
- Sketched Graph Kernel
Francesco Orsini, KU Leuven - Evolving RBF Neural Networks for Time Series Modeling Using Newton Basis
Maryam Pazouki and Dietmar P. F. Moller, TU clausthal - Speeding-up Sparse Matrix-Vector Computations and Stochastic Models in Julia
Vilen Jumutc and Johan A. K. Suykens, KU Leuven - Data Mining for System Identification: An Introduction
Yuri Shardt, Universität Duisburg-Essen - An Overview of the EnsembleSVM Software Package
Marc Claesen and Bart De Moor, KU Leuven - CryptoSwartz: Decentralized Publishing Platform and a Free Market for Peer Review
Ethan Buchman, University of Guelph and Vlad Zamfir, CoinCulture CryptoConsulting
Demonstration Session
Thursday September 11, 17.00 - 18.30Rooms S 00.04 and S 00.05
- Manopt, A Toolbox for Optimization on Manifolds
Nicolas Boumal, UCLouvain and Bamdev Mishra, University of Liège - Distributed Feature Selection and Categorization with Spark/Hadoop/Docker
Eric Charles, datalayer.io - Data Fusion with Tensorlab
Laurent Sorber, Nico Vervliet, Otto Debals, Marc Van Barel and Lieven De Lathauwer, KU Leuven - Numerical Optimal Control With CasADi
Joris Gillis, KU Leuven - Develop Fast and Deploy for Long Optimization Methods Through IBM CPLEX
Alex Fleischer, IBM Software Group - Introducing Ethereum: A General-Purpose, Decentralized, Secure Compute Platform
Ethan Buchman, University of Guelph