I was somehow led to believe that no video would be taken at ROKS 2013 ( International Workshop on Advances in Regularization, Optimization, Kernel Methods and Support Vector Machines). Well, I was wrong, it looks like the organizers contracted the videolectures folks, Here is the list of videos available from the workshop:, but first a big thank you to the organizing committee ( Johan Suykens, Andreas Argyriou, Kris De Brabanter, Moritz Diehl, Kristiaan Pelckmans, Marco Signoretto, Vanya Van Belle, Joos Vandewalle) for having the forethoughts of videotaping most of the talks. Enjoy!
- Welcome to ROKS 2013 Johan Suykens
Invited Talks
- Deep-er Kernels John Shawe-Taylor
- Connections between the Lasso and Support Vector Machines Martin Jaggi
- From Kernels to Causality Bernhard Schölkopf
- Beyond Stochastic Gradient Descent Francis R. Bach
- Domain Specific Languages for Convex Optimization Stephen P. Boyd
- Dynamic ℓ1 Reconstruction Justin Romberg
- Multi-task Learning Massimiliano Pontil
- Primal-Dual Subgradient Methods for Huge-Scale Problems Yurii Nesterov
- Living on the Edge - Phase Transitions in Random Convex Programs Joel Tropp
- Minimum Error Entropy Principle for Learning Ding-Xuan Zhou
- Learning from Weakly Labeled Data James Kwok
- The Graph-guided Group Lasso Zi Wang
- Feature Selection via Detecting Ineffective Features Kris De Brabanter
- Output Kernel Learning Methods Francesco Dinuzzo
- Deep Support Vector Machines Marco Wiering
- Subspace Learning Alessandro Rudi
- Kernel Based Identification of Systems with Multiple Outputs Using Nuclear Norm Regularization Tillmann Falck
- Fast Algorithms for Informed Source Separation Augustin Lefèvre
- Structured Low-Rank Approximation as Optimization on a Grassmann Manifold Konstantin Usevich
- Scalable Structured Low Rank Matrix Optimization Problems Marco Signoretto
- Learning with Marginalized Corrupted Features Laurens van der Maaten
- Robust Near-Separable Nonnegative Matrix Factorization Using Linear Optimization Nicolas Gillis
- Closing Johan Suykens
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