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DTSTART:20260308T070000
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DTSTART:20251102T060000
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DTSTART;TZID=America/Toronto:20260804T113000
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URL:https://uwaterloo.ca/combinatorics-and-optimization/events/optimization
 -seminar-ting-kei-pong-conditional-gradient
SUMMARY:Optimization seminar-Ting Kei Pong-A Conditional-Gradient-Based\nSi
 ngle-Loop Augmented Lagrangian Method for Inequality Constrained\nProblems
CLASS:PUBLIC
DESCRIPTION:SPEAKER:\n Ting Kei Pong\n\nAFFILIATION:\n The Hong Kong Polyte
 chnic University\n\nLOCATION:\n MC 5501\n\nABSTRACT:We consider the proble
 m of minimizing the sum of a Lipschitz\ndifferentiable convex function an
 d a proper closed convex function\nthat admits efficient linear minimiza
 tion oracles\, subject to\nmultiple smooth convex inequality constraint
 s. We adapt the\nclassical augmented Lagrangian (AL) method for these pr
 oblems: in\neach iteration\, our algorithm consists of one step of condit
 ional\ngradient (CG) method applied to the AL function\, followed by\nan
  update of the dual variable as in classical AL methods with a\ndiminish
 ing dual stepsize. We study the convergence rate of our\nalgorithm under
  two standard stepsize rules for the CG method\,\nnamely\, an open-loop s
 tepsize and the short stepsize\, and obtain a\nrate that matches the bes
 t-known complexity for this class of\nproblems. We also establish accele
 rated rates when\nthe aforementioned proper closed convex function is the
  indicator\nfunction of a uniformly convex set. This is a joint work wit
 h\nXiaozhou Wang and Zev Woodstock.
DTSTAMP:20260729T235934Z
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