Research Talks at the Zuse Institute Berlin
Welcome to the ZIB's Research Seminars and Colloquia page. Explore our schedule of research talks in mathematics and computer science. We currently host the following series at our institute:
- The Zuse Research Colloquium, a series of talks by high profile invited speakers from academia and industry.
- The Zuse Research Seminar, a series of talks by researchers from the Zuse Institute Berlin and select external speakers from the Berlin math community.
- The IOL Seminar and Lecture Series, the research seminar of the IOL research lab of Sebastian Pokutta at ZIB and TU Berlin.
For questions relating to an individual seminar or colloquium, please contact the organizers of that series. For question relating to this homepage, please contact Christoph Spiegel. The ZIB also hosts an overview of all mathematical research seminars happening in and around Berlin at seminars.zib.de.
Upcoming Talks
Riemannian optimization refers to the optimization of functions defined over Riemannian manifolds. Such problems arise when the constraints of Euclidean optimization problems can be viewed as Riemannian manifolds, such as the symmetric positive-definite cone, the sphere, or the set of orthogonal linear layers for a neural network. This Riemannian formulation enables us to leverage the geometric structure of such problems by viewing them as unconstrained problems on a manifold. The convergence rates of Riemannian optimization algorithms often rely on geometric quantities depending on the sectional curvature and the distance between iterates and an optimizer. Numerous previous works bound the latter only by assumption, resulting in incomplete analysis and unquantified rates. In this talk, I will discuss how to remove this limitation for multiple algorithms and as a result quantify their rates of convergence.
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Reliable and detailed information on forest canopy height is essential for understanding the health and carbon dynamics of forests, which play a pivotal role in climate adaptation and mitigation strategies. Traditional methods of forest monitoring, while foundational, lack the global coverage and are often costly, hindering effective policymaking. Jan Pauls and colleagues have developed a novel framework using satellite data to estimate canopy height on a global scale. The approach combines cutting-edge data preprocessing techniques, a unique loss function to mitigate geolocation inaccuracies, and data filtering from the Shuttle Radar Topography Mission to enhance prediction reliability in mountainous areas. The framework significantly improves upon existing global-scale canopy height maps. By offering a high-resolution (10 m) global canopy height map, the produced map provides critical insights into forest dynamics, aiding in more effective forest management and climate change mitigation efforts. This talk will explore the methods and implications of this work, demonstrating how advancements in Earth observation and machine learning can revolutionize global forest assessments and ecological studies.
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