User-friendly error bounds for sampling from a strongly log-concave density (more…)
9:20 – 9:45 Akiko Takeda, ISM / RIKEN AIP
Proximal DC Algorithm for Sparse Optimization (more…)
9:45 – 10:10 Francis Bach, ENS/Inria Paris
Optimal algorithms for smooth and strongly convex distributed optimization in networks (more…)
10:10 – 10:40 ——— coffee ———
10:40 – 11:05 Takanori Maehara, RIKEN AIP
Stochastic Packing Integer Programming with a Few Queries (more…)
11:05 – 11:30 Irène Waldspurger, U. Paris Dauphine
Phase retrieval with the alternating projections method (more…)
11:30 – 11:55 Taiji Suzuki, U. of Tokyo / RIKEN AIP
Generalization error bounds of deep learning by Bayesian and empirical risk minimization approaches from a kernel perspective (more…)
11:55 – 13:45 ——— Lunch – buffet served onsite
13:45 – 13:55 student talk 4: Anna Korba
A learning theory for ranking aggregation (more…)
13:55 – 14:20 Masashi Sugiyama, U. of Tokyo / RIKEN AIP
Classification from Weak Supervision (more…)