Workshop of the laboratory "High-dimensional approximation and applications" ("Sampling recovery and related problems"), 21 – 26 December 2021
We (Laboratory of High-Dimensional Approximation and Applications of the Lomonosov Moscow State University (MSU), Chemnitz Technical University, and Moscow Center of Fundamental and Applied Mathematics) are organizing an school/workshop on sampling recovery. The format is hybrid (online + Suzdal). We plan to have a 5 days school/workshop from December 21 (Tuesday) till December 26 (Sunday) of 2021. We plan to have a number of series of 2 lectures (1 hour each) on the topic accessible for students and contributed talks.
Join Zoom Meeting:
Lecture schedule (Moscow time, UTC+3 !):
Tuesday, December 21:
→ 10:00–10:45, Alexei Shadrin, "On cardinality of the lower sets and their universal discretization";
→ 10:45–11:30, Jan Vybiral, "Robust and efficient identification of neural networks", slides;
→ 11:45–12:30, Kateryna Pozharska, "Sampling recovery of multivariate functions in the uniform norm", slides.
Break
→ 15:00–16:00, Erich Novak, "Linear information versus function evaluations for \(L_2\)-approximation", slides;
→ 16:15–17:15, Vladimir Temlyakov, "Recovery in \(L_p\) norms", slides.
Wednesday, December 22:
→ 10:00–10:45, Egor Kosov, "Sampling discretization problem for \(L^1\) norm", slides;
→ 10:45–11:30, Felix Bartel, "Optimality of Cross-validation in Scattered Data Approximation", slides.
Break
→ 15:00–16:00, Karlheinz Groechenig, "From Marcinkiewicz-Zygmund inequalities to approximation theorems and quadrature rules";
→ 16:15–17:15, Mario Ullrich, "\(L_2\)-approximation based on Gaussian information, function values or other information", Lecture 1;
→ 17:30–18:30, Vladimir Temlyakov, "Recovery and discretization", slides.
Thursday, December 23:
→ 10:00–10:45, Glenn Byrenheid, "Constructive sparse approximation based on sampling";
→ 10:45–11:30, Lutz Kämmerer, "A sample efficient sparse FFT for arbitrary frequency candidate sets in high dimensions".
Break
→ 15:00–16:00, Albert Cohen, "Optimal sampling in least-squares methods - theory and practice", Lecture 1, slides;
→ 16:15–17:15, Albert Cohen, "Optimal sampling in least-squares methods - theory and practice", Lecture 2;
→ 17:30–18:30, Mark Iwen, "Sparse Fourier Transforms on Rank-1 Lattices for the Rapid and Low-Memory Approximation of Functions of Many Variables + Generalizations".
Friday, December 24:
→ 10:00–10:45, Irina Limonova, "On sampling discretization in \(L_2\)", slides;
→ 10:45–11:30, Stefan Kunis, "A survey condition number estimates for multivariate nonequispaced Fourier matrices", video.
Break
→ 14:50–15:00, Erich Novak, "Announcement", slides;
→ 15:00–16:00, Mario Ullrich, "\(L_2\)-approximation based on Gaussian information, function values or other information", Lecture 2, slides;
→ 16:15–17:15, David Krieg, "Recovering Sobolev Functions: Optimal versus Given Samples", Lecture 1, slides.
Saturday, December 25:
→ 10:00–10:45, Giovanni Migliorati, "Adaptive approximation by weighted least squares";
→ 10:45–11:30, Konstantin Rjutin, Yurii Malykhin, "The recovery of ridge functions";
→ 11:45–12:30, Michael Schmischke, "High-dimensional interpretable approximation of functions with low effictive dimension".
Break
→ 15:00–16:00, Tino Ullrich, "Implications of the Kadison Singer solution to the recovery of functions - optimal subsampling of random information", Lecture 1, slides;
→ 16:00–17:00, Tino Ullrich, "Implications of the Kadison Singer solution to the recovery of functions - optimal subsampling of random information", Lecture 2;
→ 17:15–18:15, David Krieg, "Recovering Sobolev Functions: Optimal versus Given Samples", Lecture 2.
The conference was resheduled from 3-7 May to 21-26 December.
Organizers
Vladimir Temlyakov and Tino Ullrich
Program and organizing commitee:
→ V.N. Temlyakov (chair)
→ Tino Ullrich (chair)
→ A.P. Solodov
→ E.D. Kosov
→ B.S. Kashin
→ V.E. Podolskii
→ P.A. Borodin
→ O.S. Kudryavceva
→ I.V. Limonova
Contacts: