The Workshop on Mathematical Analysis in Machine Learning will be hosted by the Department of Mathematics of the University of Pittsburgh, November 22 and 23. Registration is free, but mandatory by November 5. For questions, please reach out to Stephan Wojtowytsch.
Mathematical analysis in the broad sense (including fields such as differential geometry, partial differential equations, optimization, optimal transport, numerical analysis, stochastic analysis) has inspired algorithms in machine learning and data science ranging from spectral embeddings to diffusion models. The workshop aims to bring together experts in various topics at the intersection of analysis and machine learning and to stimulate discourse across the disciplines. We aim to
Showcase the insight gained by mathematical analysis in novel applications in machine learning and data science and the methods inspired by it.
Connect machine learning practitioners and analysts for collaboration.
Introduce mathematical analysts to the challenges and requirements of a new area of study.
Expose junior researchers to non-classical applications of mathematical analysis in a high-impact setting.
Please find the event poster here.