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DTSTART;TZID=Europe/Berlin:20241009T080000
DTEND;TZID=Europe/Berlin:20241011T160000
DTSTAMP:20240920T114250Z
CREATED:20240404T072758Z
LAST-MODIFIED:20240920T114250Z
UID:7393-1728460800-1728662400@alop.uni-trier.de
SUMMARY:Autumn School on Constrained Optimization and Machine Learning
DESCRIPTION:The Research Training Group on Algorithmic Optimization proudly announces its eighth Autumn School from October 9 – 11\, 2024. \nThis year’s focus will be on Constrained Optimization and Machine Learning \nIn today’s rapidly evolving technological landscape\, the intersection of constrained optimization and machine learning is gaining immense significance. As we tackle intricate real-world challenges\, the synergy between these two domains gets more and more important. While unconstrained optimization methods have predominantly been employed in machine learning so far\, constraints are becoming prevalent in a wide array of applications. This school offers a unique opportunity to deepen comprehension and delve into the latest advancements at the interface of the two fields. Thus\, participants will acquire invaluable skills to confront the challenges of tomorrow. \n  \nConfirmed Speakers: \nEmilio Carrizosa (University of Sevilla) – Mathematical Modeling for Counterfactual Explanations and Inverse Optimization \nTim Hoheisel (McGill University) – Regularized Least-Squares: Stability Properties and the Maximum Entropy of the Mean Method \nAndrea Lodi (Cornell University) – Machine-Learning-Augmented Mixed-Integer Programming \n  \nOrganizers: \nJan Pablo Burgard (Trier University) \nMartin Schmidt (Trier University) \nVolker Schulz (Trier University) \n  \nSchedule\, Location and Travel Information:  \n \nSchedule can be downloaded here. \nThe workshop will take place in Building E located on Campus I at Trier University. \nFor travel tips on how to get to Trier\, please check  here;\nInstructions on how to find Campus I are located here.  \n  \nRegistration information (registration is closed) \nThe registration fee of 60 € includes a welcome reception\, the conference dinner\, refreshments\, and extra-curricular activities. Detailed payment information will be communicated upon registration.  \n  \nTravel Stipend (application is closed)
URL:https://alop.uni-trier.de/event/autumn-school-on-constrained-optimization-and-machine-learning/
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:20241216T160000
DTEND;TZID=Europe/Berlin:20241216T170000
DTSTAMP:20241112T115510Z
CREATED:20241112T115510Z
LAST-MODIFIED:20241112T115510Z
UID:7632-1734364800-1734368400@alop.uni-trier.de
SUMMARY:ALOP Colloquium with Christina Schenk
DESCRIPTION:On Monday\, December 16\, 2024 at 16:00 c.t. Dr. Christina Schenk\, IMDEA Materials Insitute\, Getafe (Madrid)\, will speak at the ALOP Colloquium about her recent work. \n  \nMixed-dimensional Linked Models and Reinforcement Learning-Based Control of Reaction-Diffusion Problems \nAbstract: \nIn Mathematical modeling is a powerful tool for tackling complex challenges across various fields. For instance\, during the SARS-CoV-2 pandemic\, modeling spatial dynamics and high-diffusion pathways\, such as airways and highways\, proved essential for effective decision-making in managing the crisis. \nIn this talk\, we present two approaches to enhance modeling and decision-making. We start with linking models of different dimensionalities to represent a single physical phenomenon\, specifically coupling two diffusive models—one over a continuum and another over a curve—resulting in a mixed-dimensional problem. We establish the unconditional stability and convergence of both continuous and discrete linked models using mixed finite elements. Supported by numerical examples\, we demonstrate the benefits of combining these models and show how our methods can infer solutions from incomplete data. \nBuilding on these results\, we explore the application of reinforcement learning (RL) to automatic control problems in thermal and disease transport. We adapt a stochastic policy gradient algorithm and propose novel reward functions to guide the RL agent in interacting with a reaction-diffusion model. Our approach successfully implements control strategies despite necessary model simplifications\, showcasing the potential of RL to solve complex control problems. \nBy combining theoretical and numerical insights from mixed-dimensional modeling and machine learning\, this talk highlights new results for advancing diffusive modeling and data-driven control strategies\, opening new avenues for research in data science and control applications. \n  \nThis is joint work with Aditya Vasudevan\, David Portillo (UPM)\, Ignacio Romero\, and Maciej Haranczyk. \n  \nPlease join us at 16:00 c.t. in HS 9.
URL:https://alop.uni-trier.de/event/alop-colloquium-with-christina-schenk/
LOCATION:Trier University\, E Building\, Universitätsring 15\, Trier\, Germany
CATEGORIES:Colloquium
ORGANIZER;CN="RTG ALOP at Trier University":MAILTO:ALOP@uni-trier.de
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20250120T160000
DTEND;TZID=Europe/Berlin:20250120T170000
DTSTAMP:20250106T121301Z
CREATED:20250106T121301Z
LAST-MODIFIED:20250106T121301Z
UID:7671-1737388800-1737392400@alop.uni-trier.de
SUMMARY:ALOP Colloquium with Sonja Steffensen
DESCRIPTION:On Monday\, January 20\, 2025 at 16:00 c.t. Dr. Sonja Steffensen\, RWTH Aachen\, will speak at the ALOP Colloquium about her recent work. \n  \nRelaxation Approaches for Nonlinear Sparse Optimization Problems \nAbstract: \nIn many applications\, sparse solutions are favoured over non-sparse solutions with comparable objective value\, as for example in statistical and deep learning applications. One approach to induce sparsity relies on the l_0 norm as an additional term in the objective. Often this semicontinuous function is approximated using the continuous and convex l_1-norm as a surrogate function instead. However\, this can lead to suboptimal results with respect to the sparsity properties of the solution. \nIn this talk\, we will present an alternative exact reformulation (with respect to the l_0 norm)  using non-smooth nonlinear functions to formulate the minimization of the number of non-zero entries. The resulting problem is similar (but not equivalent) to the class of mathematical programs with complementarity constraints (MPCC). As for MPCCs relaxing the problem to a standard nonlinear program we can then apply a general nonlinear solver. In our talk we will discuss and relate the relations between the different reformulations in particular with respect to the original problem. Furthermore\, we accompany the theoretical results by some numerical tests using randomly generated data sets. \n  \nPlease join us at 16:00 c.t. in HS 9.
URL:https://alop.uni-trier.de/event/alop-colloquium-with-sonja-steffensen/
LOCATION:Trier University\, E Building\, Universitätsring 15\, Trier\, Germany
CATEGORIES:Colloquium
ORGANIZER;CN="RTG ALOP at Trier University":MAILTO:ALOP@uni-trier.de
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20250923T090000
DTEND;TZID=Europe/Berlin:20250926T170000
DTSTAMP:20250923T094025Z
CREATED:20250228T102157Z
LAST-MODIFIED:20250923T094025Z
UID:7677-1758618000-1758906000@alop.uni-trier.de
SUMMARY:International Workshop on Algorithmic Optimization
DESCRIPTION:As the research training group Algorithmic Optimization (ALOP) at Trier University enters its ninth and final year\, we are excited to host our last international workshop on algorithmic optimization. After seven successful international workshops and eight autumn schools\, this event marks a special opportunity to bring together researchers from across the field and to offer perspectives on its future evolution. \nThe workshop will feature a dynamic program\, including invited plenary talks\, contributed talks\, an engaging session with elevator pitches\, and a lively poster session. Covering the full spectrum of algorithmic optimization\, topics will range from mixed-integer programming to optimization with differential equations\, from applications in the energy sector to advancements in machine learning and data science\, as well as from foundational theory to cutting-edge algorithmic developments. \nConfirmed Invited Speakers: \nCarina Costa (State University of Maringá) \nMatthias Heinkenschloss (Rice University) \nMichael Hintermüller (WIAS Berlin) \nMartine Labbé (Université Libre de Bruxelles) \nMarina Leal (Univeritas Miguel Hernández) \nMarianna de Santis (Universitá degli Studi di Firenze) \nJohannes Thürauf (University of Technology Nuremberg) \nKathrin Welker (Helmut Schmidt University) \nOrganizers: \nMartin Schmidt (Trier University) \nVolker Schulz (Trier University) \nSchedule\, Location and Travel Information:  \n \nSchedule will be uploaded later. \nThe workshop will take place in Building E located on Campus I at Trier University. For travel tips on how to get to Trier\, please check here. Instructions on how to find Campus I are located here.  \nProgram: \nThe program and book of abstracts can be found here.
URL:https://alop.uni-trier.de/event/international-workshop-on-algorithmic-optimization/
LOCATION:Trier University\, E Building\, Universitätsring 15\, Trier\, Germany
ORGANIZER;CN="RTG ALOP at Trier University":MAILTO:ALOP@uni-trier.de
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