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X-ORIGINAL-URL:https://alop.uni-trier.de
X-WR-CALDESC:Events for ALOP
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BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20200603T121500
DTEND;TZID=Europe/Berlin:20200603T130000
DTSTAMP:20200527T094612Z
CREATED:20200526T110022Z
LAST-MODIFIED:20200527T094612Z
UID:3698-1591186500-1591189200@alop.uni-trier.de
SUMMARY:Michael Vu to speak during the research seminar
DESCRIPTION:ALOP member Michael Vu will speak during the research seminar on June 3\, 2020 at 12:15 about his work. \nPlease join as via ZOOM at 12:15 by clicking this link \n  \n 
URL:https://alop.uni-trier.de/event/michael-vu-to-speak-during-the-research-seminar/
CATEGORIES:Presentation
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20200615T170000
DTEND;TZID=Europe/Berlin:20200615T180000
DTSTAMP:20200527T102733Z
CREATED:20200526T085037Z
LAST-MODIFIED:20200527T102733Z
UID:3683-1592240400-1592244000@alop.uni-trier.de
SUMMARY:ALOP Colloquium with Prof. Andrés Gómez
DESCRIPTION:Assistant Professor Andrés Gómez of Daniel J. Epstein Department of Industrial and Systems Engineering\, University of Southern California\, will speak at our colloquium on June 15\, 2020 at 5 pm about his research via ZOOM. \nTitle: Sparse learning via mixed-integer optimization. \n  \nAbstract: This talk addresses inference problems in which sparsity plays a fundamental role. Sparse statistical models are interpretable by design and often have improved out-of-sample performance than dense models\, but learning a sparse model model from data often results in a combinatorial optimization problems. Unfortunately\, off-the-shelf mixed-integer optimization software struggle with the resulting problems\, resulting in prohibitive solution times even in small instances. We discuss techniques to improve the performance\, often related to the convexification of the underlying combinatorial problems. \nFor more details regarding the Zoom link\, please refer back to this page.
URL:https://alop.uni-trier.de/event/alop-colloquium-with-prof-andres-gomez/
CATEGORIES:Colloquium
ORGANIZER;CN="RTG ALOP at Trier University":MAILTO:ALOP@uni-trier.de
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20200617T161500
DTEND;TZID=Europe/Berlin:20200617T171500
DTSTAMP:20200615T063405Z
CREATED:20200610T115141Z
LAST-MODIFIED:20200615T063405Z
UID:3748-1592410500-1592414100@alop.uni-trier.de
SUMMARY:Mercator Fellow Matthias Heinkenschloss scheduled to lecture via ZOOM
DESCRIPTION:Research Training Group ALOP’s Mercator Fellow\, Prof. Dr. Matthias Heinkenschloss of Rice University\, will present a special lecture on Wednesday\, June 17\, 2020 at  16:15 local time via ZOOM. You may enter the waiting area beginning at 16:00. The presentation will take appr. 1 hour. \nProf. Heinkenschloss will speak on the topic of  \n  \nNumerical Solution of Risk-Averse PDE-Constrained Optimization Problems\n \nAbstract\nThis talk gives a unified presentation of several recent optimization approaches for solving risk-averse partial differential equation constrained optimization problems and addresses a numerical issue that arises in (semismooth) Newton methods used to solve subproblems in each of these approaches. Risk-averse optimization problems arise\, for example\, in engineering applications when one seeks to maximize the performance of\, or minimize the costs of a system under uncertainty. Whereas risk-neutral formulations optimize the average costs or performance\, risk-averse formulations penalize high-cost\, rare-events\, which yield excessively high costs or low performance. Risk-averse objectives like the Conditional Value-at-Risk (CVaR) are notoriously expensive to optimize due to their non-smooth nature and the inherent expense in sampling rare-events.\nThis talk focusses on the CVaR risk measure and studies recent optimization approaches which either directly smooth the CVaR or are based on a reformulation as a smooth inequality constrained problem\, such as log-barrier or augmented Lagrangian approaches. It is shown that all considered approaches solve the CVaR optimization problem by solving a sequence of smoothed CVaR optimization problems. Furthermore\, a computationally inexpensive modification of (semismooth) Newton methods is introduced that alleviates numerical issues arising from near rank deficient Hessians and inconsistent quadratic models that can arise in the smoothed CVaR subproblems.  \n \nThis talk is based on joint work with Mae Markowski.\n  \nThe ZOOM access link will be forwarded via Email.
URL:https://alop.uni-trier.de/event/mercator-fellow-matthias-heinkenschloss-scheduled-to-lecture-via-zoom/
CATEGORIES:Presentation
ORGANIZER;CN="RTG ALOP at Trier University":MAILTO:ALOP@uni-trier.de
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20200622T160000
DTEND;TZID=Europe/Berlin:20200622T170000
DTSTAMP:20200508T080832Z
CREATED:20200427T113707Z
LAST-MODIFIED:20200508T080832Z
UID:3606-1592841600-1592845200@alop.uni-trier.de
SUMMARY:ALOP-Colloquium with apl. Prof. Martin Gugat
DESCRIPTION:On Monday\, June 22. 2020 at 16:00 c.t.  apl. Prof. Martin Gugat\,  FAU Erlangen-Nuernberg will present his recent work and speak on the following topic: \n  \nThe finite time turnpike phenomenon for optimal control problems \n\nAbstract: \nOften in dynamic optimal control problems with a long time horizon\, in a large neighburhood of the middle of the time interval the optimal control and the optimal state are very close to the solution of a static control problem that is derived from the dynamic optimal control problems by omitting the information about the initial state and possibly a desired  terminal state. \nWe show that for problems with a non-smooth tracking term in the objective function that is multiplied with a sufficiently large  penalty-parameter in some cases  the optimal state and  the optimal control reach the solution of the static control problem (the so-called turnpike) exactly after finite-time and remain there  during a certain time-interval\, until close to the end of the time interval possibly the state leaves the turnpike. \nThis can be shown in different situations\, for example under exact controllability assumptions or with the assumption of nodal profile exact controllability\, as studied by Tatsien Li and his group. \n\n__________________________________________________________________________________________________________________________________________ \nTurnpike ist eine  Bezeichnung für eine Mautstrasse.  Trotz der Kosten (die Maut) werden diese Strassen oft benutzt. Da die Fahrerinnen ihren Nutzen maximieren\, muss das also unter gewissen Voraussetzungen optimal sein. \nBeim Turnpikephänomen geht es darum\, dass die Grundstruktur  einer optimalen Route über die Autobahn (zum Beispiel für einen LKW-Eiltransport von Trier nach Koblenz) für einen Startpunkt in einer Umgebung von Trier\nund einen Endpunkt in einer gewissen Umgebung von Koblenz weder vom Startpunkt noch vom Endpunkt abhängt. Die optimale Route führt zu einer Autobahnauffahrt\, bleibt dann eine gewisse Strecke auf der Autobahn und\nfährt dann am Ende wieder ab. \nEine ähnliche Struktur tritt auch bei der Lösung von dynamischen Optimalsteuerungsproblemen mit partiellen Differentialgleichungen auf\, die zum Beispiel als Modell des Betriebs von Gaspipelinenetzen verwended werden können. \n  \nThe presentation will take place remotely via Zoom. For further details and a link to the presentation please refer to this page.\n \n 
URL:https://alop.uni-trier.de/event/alop-colloquium-with-apl-prof-martin-gugat/
CATEGORIES:Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20200624T121500
DTEND;TZID=Europe/Berlin:20200624T130000
DTSTAMP:20200615T142609Z
CREATED:20200526T105906Z
LAST-MODIFIED:20200615T142609Z
UID:3696-1593000900-1593003600@alop.uni-trier.de
SUMMARY:Carina Costa to speak during the research seminar
DESCRIPTION:ALOP member Carina Costa will speak during the research seminar on  June 24\, 2020 at 12:15 on the topic \n““Decomposition Methods for Robustified $k$-Means Clustering Problems: If Less Conservative Does Not Mean Less Bad.“\n \nPlease join as via ZOOM at 12:15 . The link will be distributed via Email. \n 
URL:https://alop.uni-trier.de/event/carina-costa-to-speak-during-the-research-seminar/
CATEGORIES:Presentation
ORGANIZER;CN="RTG ALOP at Trier University":MAILTO:ALOP@uni-trier.de
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20200629T160000
DTEND;TZID=Europe/Berlin:20200629T180000
DTSTAMP:20200623T063900Z
CREATED:20200622T094133Z
LAST-MODIFIED:20200623T063900Z
UID:3790-1593446400-1593453600@alop.uni-trier.de
SUMMARY:ALOP-Colloquium with Prof. Dr. Luise Blank
DESCRIPTION:On Monday\, June 29. 2020 at 16:00 c.t.  Prof. Dr. Luise Blank with the Universitaet Regensburg will present her recent work at our colloquium entitled \nOptimization with convex constraints and an application in topology optimization \n\nThis talk focuses on projection type methods for convexly constrained optimization problems. We shortly introduce well known projection methods using the gradient in finite dimensions and summarize known results. Varying the underlying scalar product allows to include second order information to speed up the method. E.g. the projection of the Newton direction leads to a quadratic order of convergence. The method can also be interpreted as solving a sequence of optimization problems where the cost function is quadratically approximated. Results in function spaces are important to obtain methods with iteration numbers independent ot the discretization level. They also indicate which underlying metric shall be used for the projection. E.g. pde constraint problems provide often only differentiability of the cost functional in the L∞ metric. While the generalization to Hilbert spaces is straight forward the extension to Banach spaces is more involved due to the missing scalar product. We present a global convergence result for the variable metric projection type (VMPT-)method\, which allows application to nonreflexive Banach spaces and expand the possible choices of the metric. Moreover\, we give examples which fulfill the requirements on the spaces and the variable metric.\nAs an application we consider a structural topology optimization problem. The model is based on a diffuse interface ansatz using phase field variables. The necessary regularization of the cost functional with the perimeter is substituted by the Ginzburg-Landau energy. We obtain a minimization problem with pde constraints and simplex constraints for the controls. The elimination of the state using the nonlinear control-to-state operator yields a convexly constrained optimization problem\, where we can apply the VMPT-algorithm in L∞ ∩ H1. In the numerical results one can clearly see that choosing an appropriate inner product\, namely H1\, leads –in contrast to L2– to mesh independency of the iteration numbers. Including additionally second order information speeds up the method drastically. \nThe presentation will take place remotely via Zoom.  \nIf you wish to receive a link and invitation to this presentation\, please send an email to shawATuni-trier.de
URL:https://alop.uni-trier.de/event/alop-colloquium-with-prof-dr-luise-blank/
CATEGORIES:Colloquium
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