Laurent recently pointed me to the slides of a workshop that took place at IHES this past March. Here they are:
Figure from Remi Gribonval's talk.
- Ohad Shamir Trade-offs in Distributed Learning
- Alain Celisse Using kernels to detect abrupt changes in time series
- Alexandre d'Aspremont Renegar's Condition Number and Compressed Sensing Performance
- Emilie Kaufmann Optimal Best Arm Identification with Fixed Confidence
- Vianney Perchet Highly-Smooth Zero-th Order Online Optimization
- Garvesh Raskutti Algorithmic and statistical perspectives of randomized sketching for ordinary least-squares
- Pierre Alquier On the Properties of Variational Approximations of Gibbs Posteriors
- Quentin Berthet Trade-offs in Statistical Learning
- Remi Gribonval Projections, Learning, and Sparsity for Efficient Data Processing
- Silvia Villa Generalization properties of multiple passes stochastic gradient method
Liked this entry ? subscribe to Nuit Blanche's feed, there's more where that came from. You can also subscribe to Nuit Blanche by Email, explore the Big Picture in Compressive Sensing or the Matrix Factorization Jungle and join the conversations on compressive sensing, advanced matrix factorization and calibration issues on Linkedin.