Nonlinear optimization

Tuesday, August 15, 2017 - 2:00pm - 2:45pm
James Fienup (University of Rochester)
Phase retrieval has grown in popularity in recent years on account of its success in x-ray coherent diffractive imaging, including ptychography. Our development of phase retrieval for image reconstruction will be reviewed, including both passive and active imaging, in both optics and x-rays, enabling imaging from the nano-scale to the astronomical scale. Iterative transform and nonlinear optimization algorithms will be compared.
Friday, November 21, 2008 - 2:00pm - 2:45pm
Matthias Koeppe (University of California)
The classic idea to relate the maximum of a function over a
discrete or continuous domain to certain sums or integrals has
made its apppearance in a number of recent papers from the
point of view of optimization (A.I. Barvinok, Exponential
integrals and sums over convex polyhedra,
Funktsional. Anal. i Prilozhen. 26 (1992); J.B. Lasserre,
Generating functions and duality for integer programs,
Discrete Optim. 1 (2004)).

Efficient summation and integration procedures can give rise
Tuesday, January 26, 2016 - 11:30am - 12:20pm
Hongchao Zhang (Louisiana State University)
In this talk, we will discuss extending the optimal gradient methods for solving convex optimization to deal with more general nonlinear, possibly nonconvex and nonsmooth, optimization problems. These algorithms will treat the nonconvex and convex optimization problems in a unified way so that they will achieve the best known complexity for solving a more general class of optimization problems.
Both the well-studied techniques for nonlinear programming and the techniques
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