SCHEDULE

8:15 - 9:00 Coffee, Juice, Bagels, Fruit, and Pastries

• Morning Session Talks (9 - 12)
  • 9:00 - 9:45: Levent Tuncel , University of Waterloo, Waterloo
                       " Fundamentals of Convergence Theories for Convex Relaxation Hierarchies "

  • 9:45 - 10:00: Valentin Koch , University of British Columbia, Okanagan
                       " Convexity of the proximal average "

  • 10:00 - 10:15: Bryan Gardiner , University of British Columbia, Okanagan
                       " Numerical Computation of Fitzpatrick Functions "

  • 10:15 - 10:30: Coffee Break

  • 10:30 - 11:00: Zhaosong Lu , Simon Fraser University, Surrey
                       " An Augmented Lagrangian Approach for Sparse Orthogonal Principle Component Analysis "

  • 11:00 - 11:20: Ying Wang , Simon Fraser University, Burnaby
                       " Techniques for Benchmarking of Optimization Algorithms: A Case Study Using Line Search Variants of the Nelder-Mead Algorithm "

  • 11:20 - 12:00: Defeng Sun , National University of Singapore
                       " A proximal point method for matrix least squares problem with nuclear norm regularization "

• 12:00 - 1:30 Lunch Break

• Afternoon Session Talks (1:30 - 3:15)
  • 1:30: - 2:15 Jiawang Nie , University of California, San Diego
                       " SDP Representation of Convex Sets "

  • 2:15 - 2:30: Liangjin Yao , University of British Columbia, Okanagan
                       " On the maximal monotonicity of the sum of a maximal monotone linear operator and a normal cone operator "

  • 2:30 - 2:45: Onur H. Mete , University of Washington, Seattle
                       " Pattern Discrete and Mixed Hit-and-Run for Global Optimization and Mixed Integer Programming "

  • 2:45 - 3:00: Wei (Chris) Wang , University of Washington, Seattle
                       " Adaptive Parameterized Improving Hit-and-Run for Global Optimization "

  • 3:00 - 3:15: Julie Eaton , University of Washington, Seattle
                       " Globally robust methods for constrained nonlinear programming "