Slides: Computational and statistical trade-offs in learning @IHES

 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

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