This student-run reading group meets weekly to discuss methods and applications of optimization.

Here is a list of resources which group members have recommended.

Boyd's Convex Optimization Video Lectures

Hastie, Tibshirani & Wainwright Statistical Learning with sparsity Primarily about Lasso and its generalizations from a statistical perspective.

Off the Convex Path A blog with reflections on the methods of convex optimization.

I'm a Bandit A blog on Probability, Optimization, and Statistics. The “Complexities of Optimization” course notes on this site are a great introduction to research-level optimization.

For Spring 2017, the seminar is held on Fridays from 3:10-4:00p in MSB 3240.

Dates:

• 4/7: No seminar (SIAM regional meeting)
• 4/14: Robert: Regularization using Total Variation
• 4/21: Jiawei: Dual Feasible Functions for Integer Programming
• 4/28: Will: Three Excursions around Conic Duality
• 5/5: Gabe
• 5/12: No seminar (BayOpt conference)
• 5/19: David H
• 5/26: Yunshen
• 6/2: Ji
• 6/8: Julio/David W

Winter 2017:

• 1/19: Roundtable talks
• 1/26: Julio: Royset, Johannes O., and Roger JB Wets. "Variational Theory for Optimization under Stochastic Ambiguity." (2016).
• 2/2: David H: Park, J. and Boyd, S. "Concave Quadratic Cuts for Mixed-Integer Quadratic Problems." (2015).
• 2/9: David W: See the text by Hastie et al. Also see Website for GLMNet package.
• 2/17 (3p): Robert Douglas-Rachford Splitting in the Context of Proximal Point Algorithms
• 2/23: Ji: Rong Ge, Jason D. Lee, and Tengyu Ma. "Matrix Completion has No Spurious Local Minimum"
• 3/2: Will: Eriksson, Olsson, Kahl. "Normalized Cuts Revisited: A Reformulation for Segmentation with Linear Grouping Constraints"
• 3/10 (3p): Yiqun: Hastie, Tibshirani & Wainwright Statistical Learning with sparsity
• 3/16: Mikhail: Multi-Objective Optimization Using Evolutionary Algorithms