ARCO Lab at the Midwest Optimization Meeting

The folks at ARCO Lab were delighted to attend the 26th Midwest Optimization Meeting (MOM26) on Friday, Nov. 9th and Saturday, Nov. 10th at The University of Waterloo. As roboticists interested in applying optimization theory, we learned a great deal, including how to think about Bayesian D-optimality as a special case of a more general problem, the foundations of convex optimization in Hadamard spaces, how to improve the statistical efficiency of stochastic gradient descent, and the great R. Tyrrell Rockafellar’s latest thoughts on decomposing optimization problems. Thank you to the organizers for coordinating an incredibly interesting lineup of speakers and posters!