01-Apr Francis Bach INRIA
Finding Global Minima via Kernel Approximations
08-Apr Joel Tropp Caltech
Scalable semidefinite programming
15-Apr Yuxin Chen Princeton
Demystifying the Efficiency of Reinforcement Learning: Two Recent Stories
22-Apr Yihong Wu Yale
Recent results in planted assignment problems
29-Apr Kunal Talwar Apple
Private Stochastic Convex Optimization
06-May Aaron Sidford Stanford
Interior Point Methods for Nearly Linear Time Algorithms
13-May Csaba Szepesvari University of Alberta
[POSTPONED to 10-June-2021] Between tractable and intractable problems in reinforcement learning
20-May Inderjit S. Dhillon UT Austin
Multi-Scale Methods for Machine Learning
27-May Aarti Singh Carnegie Mellon University
Learning from preferences and labels
03-Jun Mert Pilanci Stanford
The Hidden Convex Optimization Landscape of Deep Neural Networks
10-Jun Csaba Szepesvari University of Alberta
Between tractable and intractable problems in reinforcement learning