Join us to hear some new, exciting work at the intersection of optimization and ML. Come and ask questions and join the discussion.

Speakers: Samuel Horvath, "Adaptivity of Stochastic Gradient Methods for Nonconvex Optimization" Guan-Horng Liu, "DDPNOpt: Differential Dynamic Programming Neural Optimizer" Nicolas Loizou, "Stochastic Polyak Step-size for SGD: An Adaptive Learning Rate for Fast Convergence" Sharan Vaswani, "Adaptive Gradient Methods Converge Faster with Over-Parameterization (and you can do a line-search)" Sharan Vaswani, "How to make your optimizer generalize better"

You can find a video on the NeurIPS website where the speakers discuss in detail their paper.