Optimization group meeting (Spring 2019)

Time: 14:00 - 16:00 on Wednesdays

Location: Amos Eaton Hall 411

Participants

Regular participants: Profs. Rongjie Lai, John Mitchell, and Yangyang Xu's group members.

For others: anyone is welcome to join us if you are interested in the topic to be presented.

Schedules

• April 24: Yibo Xu, Level-Set Methods for Finite-Sum Constrained Convex Optimization

• April 17: Colin Sutcher-Shepard GIANT: Globally Improved Approximate Newton Method for Distributed Optimization

• April 10: Yonggui Yan, The Marginal Value of Adaptive Gradient Methods in Machine Learning and Closing the Generalization Gap of Adaptive Gradient Methods in Training Deep Neural Networks

• April 3: Yibo Xu, Optimal Black-Box Reductions Between Optimization Objectives

• March 27: Colin Sutcher-Shepard,Asynchronous Decentralized Parallel Stochastic Gradient Descent

• March 20: Gabe Mancino-Ball, Efficient Global Optimization of Expensive Black-Box Functions

• March 13: Zichong Li, Accelerated regularized Newton methods for minimizing composite convex functions

• Feb. 13: Colin Sutcher-Shepard, Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization

• Feb. 06: Zichong Li, Iteration Complexity of Feasible Descent Methods for Convex Optimization

• Jan. 30: Yibo Xu, Accelerated Method for Stochastic Composition Optimization with Nonsmooth Regularization

• Jan. 23: Yonggui Yan, Randomized Linear Programming Solves the Discounted Markov Decision Problem In Nearly-Linear (Sometimes Sublinear) Running Time