BEGIN:VCALENDAR VERSION:2.0 PRODID:researchseminars.org CALSCALE:GREGORIAN X-WR-CALNAME:researchseminars.org BEGIN:VEVENT SUMMARY:Frank E. Curtis (Lehigh University) DTSTART:20210315T143000Z DTEND:20210315T153000Z DTSTAMP:20260423T021008Z UID:OWOS/40 DESCRIPTION:Title: SQ P Methods for Deterministically Constrained Stochastic Optimization\nb y Frank E. Curtis (Lehigh University) as part of One World Optimization se minar\n\n\nAbstract\nStochastic gradient and related methods for solving s tochastic optimization problems have been studied extensively in recent ye ars. It has been shown that such algorithms and much of their convergence and complexity guarantees extend in straightforward ways when one conside rs problems involving simple constraints\, such as when one can perform pr ojections onto the feasible region of the problem. However\, settings wit h general nonlinear constraints have received less attention\, and many of the approaches that have been proposed for solving such problems resort t o using penalty or (augmented) Lagrangian methods\, which are often not th e most effective strategies. In this work\, we propose and analyze stocha stic optimization algorithms for deterministically constrained problems ba sed on the sequential quadratic optimization (commonly known as SQP) metho dology. We discuss the rationale behind our proposed techniques\, converg ence in expectation and complexity guarantees for our algorithms\, and the results of preliminary numerical experiments that we have performed.\n\nT he address and password of the zoom room of the seminar are sent by e-mail on the mailinglist of the seminar one day before each talk\n LOCATION:https://researchseminars.org/talk/OWOS/40/ END:VEVENT END:VCALENDAR