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Session II.2 - Continuous Optimization

Thursday, June 15, 15:00 ~ 15:30

Adaptive Stochastic Algorithms for Nonlinearly Constrained Optimization

Frank E. Curtis

Lehigh University, USA   -   This email address is being protected from spambots. You need JavaScript enabled to view it.

I will discuss the interesting features that drive the convergence guarantees for a set of adaptive stochastic algorithms that my collaborators and I have proposed for solving nonlinearly constrained optimization problems. These algorithms are of the sequential quadratic optimization and interior-point varieties, and they operate in the fully stochastic regime in which we prove convergence-in-expectation and almost-sure-convergence guarantees.

Joint work with Albert S. Berahas (University of Michigan, USA), Xin Jiang (Lehigh University, USA), Michael J. O'Neill (University of North Carolina, USA), Daniel P. Robinson (Lehigh University, USA), Qi Wang (Lehigh University, USA) and Baoyu Zhou (University of Chicago, USA).

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