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DTSTART;TZID=Europe/Berlin:20231204T160000
DTEND;TZID=Europe/Berlin:20231204T170000
DTSTAMP:20231024T083813Z
CREATED:20230814T123308Z
LAST-MODIFIED:20231024T083813Z
UID:7275-1701705600-1701709200@alop.uni-trier.de
SUMMARY:ALOP Colloquium with Marc Pfetsch
DESCRIPTION:On Monday\, December 4\, 2023 at 16:00 c.t. Prof. Dr. Marc Pfetsch\, TU Darmstadt\, will speak at the ALOP Colloquium about his recent work: \n  \nCombinatorial Aspects of Physical Networks \nAbstract:\n \nThis talk considers combinatorial properties of physical networks like water\, gas\, heat\, and electrical networks. One common model are potential-based flows\, for which\, in general\, the corresponding flows depend in a nonlinear way on potentials (e.g.\, pressures) and are unique. The talk will discuss two different topics. The first is how the fact that flows in physical networks are acyclic can be used to strengthen mixed-integer optimization formulations and to derive combinatorial models. The second concerns the recovery of the structure of the network\, given only information at the entries and exits. The talk will demonstrate positive and negative results in this direction. \n  \nPlease join us at 16:00 c.t. in HS 9.
URL:https://alop.uni-trier.de/event/alop-colloquium-with-marc-pfetsch/
LOCATION:Trier University\, E Building\, Universitätsring 15\, Trier\, Germany
CATEGORIES:Colloquium
ORGANIZER;CN="RTG ALOP at Trier University":MAILTO:ALOP@uni-trier.de
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BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20231207T160000
DTEND;TZID=Europe/Berlin:20231207T170000
DTSTAMP:20231123T093046Z
CREATED:20231123T093046Z
LAST-MODIFIED:20231123T093046Z
UID:7328-1701964800-1701968400@alop.uni-trier.de
SUMMARY:ALOP Colloquium with Falk Hante
DESCRIPTION:On Thursday\, December 7\, 2023 at 16:00 c.t. Prof. Dr. Falk Hante\, will speak at the ALOP Colloquium about his recent work: \n  \nTime-Domain Decomposition for Mixed-Integer Optimal Control Problems \nAbstract:\n \nWe consider mixed-integer optimal control problems\, whose optimality conditions involve global combinatorial optimization aspects for the corresponding Hamiltonian pointwise in time. We propose a time-domain decomposition\, which makes this problem class accessible for mixed-integer programming using parallel-in-time direct discretizations. The approach is based on a decomposition of the optimality system and the interpretation of the resulting subproblems as suitably chosen mixed-integer optimal control problems on subintervals in time. An iterative procedure then ensures continuity of the states at the boundaries of the subintervals via co-state information encoded in virtual controls. We prove convergence of this iterative scheme for discrete-continuous linear-quadratic problems and present numerical results both for linear-quadratic as well as nonlinear problems. \n  \nPlease join us at 16:00 c.t. in HS 9.
URL:https://alop.uni-trier.de/event/alop-colloquium-with-falk-hante/
LOCATION:Trier University\, E Building\, Universitätsring 15\, Trier\, Germany
ORGANIZER;CN="RTG ALOP at Trier University":MAILTO:ALOP@uni-trier.de
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20231211T160000
DTEND;TZID=Europe/Berlin:20231211T170000
DTSTAMP:20230906T085744Z
CREATED:20230814T123248Z
LAST-MODIFIED:20230906T085744Z
UID:7277-1702310400-1702314000@alop.uni-trier.de
SUMMARY:ALOP Colloquium with Mathias Staudigl
DESCRIPTION:On Monday\, December 11\, 2023 at 16:00 c.t. Prof. Dr. Mathias Staudigl\, University of Mannheim\, will speak at the ALOP Colloquium about his recent work: \n  \nA regularized variance-reduced modified extragradient method for stochastic hierarchical games \nAbstract:\n \nThe theory of learning in games has so far focused mainly on games with simultaneous moves. Recently\, researchers in machine learning have started investigating learning dynamics in games involving hierarchical decision-making. We consider an N-player hierarchical game in which the ith player’s objective comprises of an expectation-valued term\, parametrized by rival decisions\, and a hierarchical term. Such a framework allows for capturing a broad range of stochastic hierarchical optimization problems\, Stackelberg equilibrium problems\, and leader-follower games. We develop an iteratively regularized and smoothed variance-reduced modified extragradient framework for learning hierarchical equilibria in a stochastic setting. We equip our analysis with rate statements\, complexity guarantees\, and almost-sure convergence claims. We then extend these statements to settings where the lower-level problem is solved inexactly and provide the corresponding rate and complexity statements. \n  \nPlease join us at 16:00 c.t. in HS 9.
URL:https://alop.uni-trier.de/event/alop-colloquium-with-mathias-staudigl/
LOCATION:Trier University\, E Building\, Universitätsring 15\, Trier\, Germany
CATEGORIES:Colloquium
ORGANIZER;CN="RTG ALOP at Trier University":MAILTO:ALOP@uni-trier.de
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