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DTSTAMP:20221202T164621
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SUMMARY:Talk of Dr. Michael Mühlebach
DESCRIPTION:Dr. Michael Mühlebach\nMax Planck Institute for Intelligent Systems\nTübingen, Germany  \nTuesday 2022-12-13 4 p.m.\nIST Seminar Room 2.255 - Pfaffenwaldring 9 - Campus Stuttgart-Vaihingen  \nAbstract\nMy talk will highlight connections between dynamical systems and\noptimization and will be divided into two parts: The first part presents an analysis of accelerated\nfirst-order optimization algorithms, where the continuous dependence of iterates with respect to\ntheir initial conditions will be exploited for characterizing the convergence rate. The result\nestablishes criteria for accelerated convergence of a large class of momentum-based optimization\nalgorithms. The criteria, which are easily verifiable, are necessary and sufficient and therefore\nprecisely characterize optimization algorithms that are accelerated. The analysis applies to\nnon-convex functions, unifies discrete-time and continuous-time models, and rigorously explains why\nstructure-preserving (symplectic) discretization schemes are important in optimization. The second\npart of the talk introduces a class of first-order methods for constrained optimization that are\nbased on an analogy to non-smooth dynamical systems. The key underlying idea is to express\nconstraints in terms of velocities instead of positions, which has the algorithmic consequence that\noptimizations over feasible sets at each iteration are replaced with optimizations over local,\nsparse convex approximations. The result is a simplified suite of algorithms and an expanded range\nof possible applications in machine learning.  \nBiographical Information\nMichael Muehlebach studied mechanical engineering at ETH Zurich. He received his Ph.D. under the\nsupervision of Prof. R. D'Andrea in 2018 and joined the group of Prof. Michael I. Jordan at the\nUniversity of California, Berkeley as a postdoctoral researcher. In 2021 he started as an\nindependent group leader at the Max Planck Institute for Intelligent Systems in Tuebingen, where he\nleads the group "learning and dynamical systems".\nHe is interested in a variety of subjects, including machine learning, dynamical systems, and\noptimization. \nHe received the Outstanding D-MAVT Bachelor Award for his Bachelor's degree and the Willi-Studer\nprize for the best Master's degree. His Ph.D. thesis was awarded with the ETH Medal and the HILTI\nprize for innovative research. He was also awarded a Branco Weiss Fellowship and an Emmy Noether\nFellowship, which fund his research group. 
DTSTART;TZID=Europe/Berlin;VALUE=DATE:20221213
URL;VALUE=URI:https://www.ist.uni-stuttgart.de/events/Talk-of-Dr.-Michael-Muehlebach/
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