Campuses:

value functions

Thursday, May 10, 2018 - 11:00am - 11:50am
Nicolai Krylov (University of Minnesota, Twin Cities)
We show that the value function in a stochastic differential game does not change if we keep the same space $(\Omega,\cF)$ but introduce probability measures by means of Girsanov's transformation {\em depending\/} on the policies of the players. We also show that the value function does not change if we allow the driving Wiener processes to depend on the policies of the players. Finally, we show that the value function does not change if we perform a random time change with the rate depending on the policies of the players.
Wednesday, January 27, 2016 - 2:00pm - 2:50pm
Michael Friedlander (University of California)
Convex optimization problems in a variety of applications have favorable objectives but complicating constraints, and first-order methods are not immediately applicable. We describe an approach that exchanges the roles of the objective and constraint functions, and instead approximately solves a sequence of parametric problems. We describe the theoretical and practical properties of this approach for a broad range of problems, including sparse and conic optimization.

Joint work with A. Aravkin, J. Burke, D. Drusvyatskiy, and S. Roy.
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