Programme > Planning

Semaine Lun. 08 Mar. 09 Mer. 10 Jeu. 11 Ven. 12 Liste

	Lun. 08	Mar. 09	Mer. 10	Jeu. 11	Ven. 12
08:00 09:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00	Inscription - Café & croissant 8:00 - 9:15 (1h15) Inscription - Café & croissant Accueil 9:15 - 9:25 (10min) Accueil A22 Amphi Wegener Guy Melançon Signal processing on graphs for applications in machine learning and network science 9:25 - 10:25 (1h) Signal processing on graphs for applications in machine learning and network science A22 Amphi Wegener Pierre Vandergheynst Compressed sensing and low rank matrix recovery (invited) Analyse de Gabor 10:25 - 12:30 (2h05) Compressed sensing and low rank matrix recovery (invited) A22 Amphi Wegener Felix Kramer & Richard Kueng › Matrix Completion with Selective Sampling - 10:25-10:50 (25min) › Entropy Estimates on Tensor Products of Banach Spaces and Applications to Low-Rank Recovery - 10:50-11:15 (25min) › New Algorithms and Improved Guarantees for One-Bit Compressed Sensing on Manifolds - Rayan Saab, University of California, Sans Diego 11:15-11:40 (25min) › Completion of Structured Low-Rank Matrices via Iteratively Reweighted Least Squares - Christian Kümmerle, TU Munich 11:40-12:05 (25min) › Robust Recovery of Sparse Non-negative Weights from Mixtures of Positive-Semidefinite Matrices - Peter Jung, TU Berlin 12:05-12:30 (25min) 10:25 - 12:30 (2h05) Analyse de Gabor A22 Amphi Edison Volker Pohl › Signal transmission through an unidentified channel - Dae Gwan Lee, Katholische Universitat Eichstatt-Ingolstadt 10:25-10:50 (25min) › A quantitative Balian-Low theorem for subspaces - Andrei Caragea, Katholische Universitaet Eichstaett-Ingolstadt 10:50-11:15 (25min) › Time-Frequency Shift Invariance of Gabor Spaces - Friedrich Philipp, Katholische Universitaet Eichstaett-Ingolstadt 11:15-11:40 (25min) › Adaptive Frames from Quilted Local Time-Frequency Systems - Gino Angelo Velasco, University of the Philippines, Diliman 11:40-12:05 (25min) › On the smoothness of dual windows for Gabor windows supported on [-1; 1] - Kamilla H. Nielsen, Technical University of Denmark [Lyngby] 12:05-12:30 (25min) Déjeuner 12:30 - 14:00 (1h30) Déjeuner Sharpness, Restart and Compressed Sensing Performance 14:00 - 15:00 (1h) Sharpness, Restart and Compressed Sensing Performance A22 Amphi Wegener Alexandre d'Aspremont https://sampta2019.sciencesconf.org/data/program/Aspremont.pdf Frame theory (invited) Reconstruction de Phase 15:00 - 16:15 (1h15) Frame theory (invited) A22 Amphi Wegener John Jasper & Dustin Mixon › Equi-isoclinic subspaces from difference sets - Matthew Fickus, Air Force Intitute of Technology 15:00-15:25 (25min) › Exact Line Packings from Numerical Solutions - 15:25-15:50 (25min) › 2- and 3-Covariant Equiangular Tight Frames - Emily King, Bremmen U. 15:50-16:15 (25min) 15:00 - 16:15 (1h15) Reconstruction de Phase A22 Amphi Edison Gert Tamberg › Conjugate Phase Retrieval in Paley-Wiener Space - Eric S. Weber, Iowa State University 15:00-15:25 (25min) › Phase Retrieval for Wide Band Signals - Rolando Perez III, Institut de Mathématiques de Bordeaux 15:25-15:50 (25min) › Dual-Reference Design for Holographic Phase Retrieval - David A. Barmherzig, Stanford University 15:50-16:15 (25min) Pause café 16:15 - 16:45 (30min) Pause café Frame theory (invited) Méthodes probabilistes 16:45 - 17:35 (50min) Frame theory (invited) A22 Amphi Wegener John Jasper & Dustin Mixon › The Zak transform and representations induced from characters of an abelian subgroup - Joseph W. Iverson, Iowa State 16:45-17:10 (25min) › A Delsarte-Style Proof of the Bukh-Cox Bound - 17:10-17:35 (25min) 16:45 - 18:00 (1h15) Méthodes probabilistes A22 Amphi Edison Holger Rauhut › Non-Gaussian Random Matrices on Sets: Optimal Tail Dependence and Applications - Halyun Jeong, University of British Columbia 16:45-17:10 (25min) › Fast Multitaper Spectral Estimation - Santhosh Karnik, Georgia Tech 17:10-17:35 (25min)	Metric repair on manifolds with holes 8:30 - 9:30 (1h) Metric repair on manifolds with holes A22 Amphi Wegener Anna Gilbert (University of Michigan) https://sampta2019.sciencesconf.org/data/program/Gilbert_1.pdf Pause café 9:30 - 10:00 (30min) Pause café Time-frequency analysis (invited) Echantillonage compressé Deep Learning 10:05 - 12:10 (2h05) Time-frequency analysis (invited) A9 Amphi 1 Antti Haimi & José-Luis Romero › The Strohmer and Beaver Conjecture for Gaussian Gabor Systems - A Deep Mathematical Problem (?) - Markus Faulhuber, University of Vienna [Vienna] 10:05-10:30 (25min) › Scaling limits in planar eigenvalue ensembles - Yacin Ameur, Lund University 10:30-10:55 (25min) › A correspondence between zeros of time-frequency transforms and Gaussian analytic functions - Rémi Bardenet, CNRS, Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189 10:55-11:20 (25min) › The Diamond ensemble: a well distributed family of points on S2 - 11:20-11:45 (25min) › Filtering the Continuous Wavelet Transform Using Hyperbolic Triangulations - Günther Koliander, University of Vienna [Vienna] 11:45-12:10 (25min) 10:05 - 12:10 (2h05) Echantillonage compressé A9 amphi 2 Simon Foucart › Multiplication-free coordinate descent iteration for l1-regularized least squares - Nguyen T. Thao, City College New York 10:05-10:30 (25min) › Random Gabor Multipliers and Compressive Sensing - Georg Tauböck, Austrian Accademy of Science 10:30-10:55 (25min) › Parameter Instability Regimes in Sparse Proximal Denoising Programs - Aaron Berk, British Columbia 10:55-11:20 (25min) › Phase transition for eigenvalues and recovery of rank one matrices - Enrico Au-Yeung, De Paul 11:20-10:45 (-1h-35) › Sparse synthesis regularization with deep neural networks - Daniel Obmann, University of Innsbruck 11:45-12:10 (25min) 10:05 - 12:10 (2h05) Deep Learning A9 Amphi 3 Mahya Ghandehari › Projection-Based 2.5D U-net Architecture for Fast Volumetric Segmentation - Christoph H. Angermann, University of Innsbruck 10:05-10:30 (25min) › Unfavorable structural properties of the set of neural networks with fixed architecture - Mones Raslan, Technishe Universität Berlin 10:30-10:55 (25min) › Towards a Regularity Theory for ReLU Networks - Chain Rule and Global Error Estimates - 10:55-11:20 (25min) › A Rate-Distortion Framework for Explaining Deep Neural Network Decisions - Stephan Wäldchen, TU Berlin 11:20-11:45 (25min) › Deep-Sparse Array Cognitive Radar - Satish Mulleti, Weizmann Institute of Science 11:45-12:10 (25min) déjeuner 12:10 - 13:45 (1h35) déjeuner Combinatorial compressed sensing with expanders 13:45 - 14:45 (1h) Combinatorial compressed sensing with expanders A22 Amphi Wegener Bubacarr Bah https://sampta2019.sciencesconf.org/data/program/Bah.pdf Deep learning (invited) Théorie des "Frames" Reconstruction de Phase 14:55 - 16:10 (1h15) Deep learning (invited) A9 Amphi 1 Misha Belkin & Mahdi Soltanolkotabi › Reconciling modern machine learning practice and the classical bias-variance trade-off - 14:55-15:20 (25min) › Overparameterized Nonlinear Optimization with Applications to Neural Nets - Samet Oymak, University of California, Riverside 15:20-15:45 (25min) › General Bounds for 1-Layer ReLU approximation - Bolton R. Bailey, University of Illinois at Urbana-Champaign [Urbana] 15:45-16:10 (25min) 14:55 - 16:10 (1h15) Théorie des "Frames" A9 amphi 2 Ole Christensen › Banach frames and atomic decompositions in the space of bounded operators on Hilbert spaces - Peter Balazs, Austrian Academy of Sciences 14:55-15:20 (25min) › Frames by Iterations in Shift-invariant Spaces - Diana Carbajal, Universidad de Buenos Aires [Buenos Aires] 15:20-15:45 (25min) › Frame representations via suborbits of bounded operators - Ole Christensen, Technical University of Denmark 15:45-16:10 (25min) 14:55 - 16:10 (1h15) Reconstruction de Phase A9 Amphi 3 Jo Lakey › Phase Estimation from Noisy Data with Gaps - Yitong Huang, Dartmouth College 14:55-15:20 (25min) › Phase retrieval from local correlation measurements with fixed shift length - 15:20-15:45 (25min) › Ill-conditionedness of discrete Gabor phase retrieval and a possible remedy - Matthias Wellershoff, ETH Zurich 15:45-16:10 (25min) Deep learning (invited) Quantisation Théorie des "Frames" 16:20 - 17:10 (50min) Deep learning (invited) A9 Amphi 1 Misha Belkin & Mahdi Soltanolkotabi › Generalization in deep nets: an empirical perspective - Tom Goldstein, University of Maryland 16:20-16:45 (25min) › Neuron birth-death dynamics accelerates gradient descent and converges asymptotically - Joan Bruna, Courant Institute of Mathematical Sciences [New York] 16:45-17:10 (25min) 16:20 - 17:35 (1h15) Quantisation A9 Amphi 3 Ozgur Yilmaz › Higher order 1-bit Sigma-Delta modulation on a circle - 16:20-16:45 (25min) › One-Bit Compressed Sensing Using Smooth Measure of l0 Norm - Arash Amini, Sharif University of Technology 16:45-17:10 (25min) › Monte Carlo wavelets: a randomized approach to frame discretization - Zeljko Kereta, Simula Research Lab 17:10-17:35 (25min) 16:20 - 17:35 (1h15) Théorie des "Frames" A9 amphi 2 Ole Christensen › Sum-of-Squares Optimization and the Sparsity Structure of Equiangular Tight Frames - Dmitriy Kunisky, Courant Institute of Mathematical Sciences [New York] 16:20-16:45 (25min) › Frame Potentials and Orthogonal Vectors - Josiah Park, Georgia Tech 16:45-17:10 (25min) › Compactly Supported Tensor Product Complex Tight Framelets with Directionality - Xiaosheng Zhuang, City University Hong Kong 17:10-17:35 (25min) Poster & Welcome Party 17:45 - 20:00 (2h15) Poster & Welcome Party Haut Carré › A directional periodic uncertainty principle - Elena Lebedeva, Saint-Petersburg State University 18:00-20:00 (2h) › A Joint Deep Learning Approach for Automated Liver and Tumor Segmentation - Nadja Gruber, University of Innsbruck 18:00-20:00 (2h) › Adapted Decimation on Finite Frames for Arbitrary Orders of Sigma-Delta Quantization - Kung-Ching Lin, University of Maryland 18:00-20:00 (2h) › Adaptive Rate EEG Signal Processing for Epileptic Seizure Detection - Saeed Qaisar, Effat University 18:00-20:00 (2h) › Brain Activity Estimation using EEG-only Recordings Calibrated with joint EEG-fMRI Recordings using Compressive Sensing - Ataei Ali, Sharif University of Technology 18:00-20:00 (2h) › Compressed Diffusion - Scott Gigante, Computational Biology and Bioinformatics Program, Yale University 18:00-20:00 (2h) › Compressive Sampling and Least Squares based Reconstruction of Correlated Signals - Ali Ahmed, Information Technology University 18:00-20:00 (2h) › Construction of Non-Uniform Parseval Wavelet Frames for L^2(R) via UEP - Hari Hari Krishan Malhotra, University of Dehli 18:00-20:00 (2h) › Deterministic matrices with a restricted isometry property for partially structured sparse signals - Alihan Kaplan, TU Munich 18:00-20:00 (2h) › Frame Bounds for Gabor Frames in Finite Dimensions - Palina Salanevich, UCLA 18:00-20:00 (2h) › Lagrange interpolation of bandlimited functions on slowly increasing sequences - Louie John VALLEJO, Institute of Mathematics, University of the Philippines - Diliman 18:00-20:00 (2h) › Near optimal polynomial regression on norming meshes - Marco Vianello, University of Padova 18:00-20:00 (2h) › Network Tomography in Hyperbolic Space - Stephen D. Casey, American University Washington 18:00-20:00 (2h) › Nonuniform Sampling of Echoes of Light - Miguel Heredia Conde, University of Siegen 18:00-20:00 (2h) › NP-hardness of L0 minimization problems: revision and extension to the non-negative setting - Thi-Thanh Nguyen, Université de Lorraine 18:00-20:00 (2h) › On Column-Row Matrix Approximations - Keaton Hamm, University of Arizona 18:00-20:00 (2h) › On Inferences from Completed Data - Jamie Haddock, UCLA 18:00-20:00 (2h) › On Kantorovich-type sampling operators - 18:00-20:00 (2h) › Passive and Active Sampling for Piecewise-Smooth Graph Signals - Rohan Varma, Carnegie Mellon University 18:00-20:00 (2h) › Random Diffusion Representations - Moshe Salhov, Tel Aviv University 18:00-20:00 (2h) › Reconstructing high-dimensional Hilbert-valued functions via compressed sensing - Nicholas C. Dexter, Simon Fraser University and PIMS 18:00-20:00 (2h) › Recovery of a class of Binary Images from Fourier Samples - 18:00-20:00 (2h) › Sampling and Recovery of Binary Shapes via Low-Rank structures - Arash Amini, Sharif University of Technology 18:00-20:00 (2h) › Unitarization and Inversion Formula for the Radon Transform for Hyperbolic Motions - Francesca Bartolucci, Università di Genova 18:00-20:00 (2h)	Approximation by crystal invariant subspaces 8:30 - 9:30 (1h) Approximation by crystal invariant subspaces A22 Amphi Wegener Ursula Molter https://sampta2019.sciencesconf.org/data/program/Molter.pdf Pause café 9:30 - 10:00 (30min) Pause café Phase Retrieval (invited) Traitement du signal non-euclidéen (graphes, variétés,...) 10:05 - 12:10 (2h05) Phase Retrieval (invited) A9 Amphi 1 Tom Goldstein & Irène Waldspurger › 3D Phaseless Imaging at Nano-scale: Challenges and Possible Solutions - Mahdi Soltanolkotabi, University of Soutern California 10:05-10:30 (25min) › Optimally Sample-Efficient Phase Retrieval with Deep Generative Models - Oscar Leong, Rice University 10:30-10:55 (25min) › The Cramer-Rao Lower Bound in the Phase Retrieval Problem - Radu Balan, University of Maryland 10:55-11:20 (25min) › Stability of Phase Retrieval Problem - Palina Salanevich, UCLA 11:20-11:45 (25min) › PhasePack: A Phase Retrieval Library - Tom Goldstein, University of Maryland 11:45-12:10 (25min) 10:05 - 12:10 (2h05) Traitement du signal non-euclidéen (graphes, variétés,...) A9 amphi 2 Elena Lebedeva › Generalized Sampling on Graphs With A Subspace Prior - Yuichi Tanaka, Tokyo University of Agriculture and Technology 10:05-10:30 (25min) › Numerical computation of eigenspaces of spatio-spectral limiting on hypercubes - Joseph Lakey, New Mexico State University 10:30-10:55 (25min) › On the Transferability of Spectral Graph Filters - Ron Levie, TU Berlin 10:55-11:20 (25min) › Sampling on Hyperbolic Surfaces - Stephen D. Casey, American University Washington 11:20-11:45 (25min) › Random Sampling for Bandlimited Signals on Product Graphs - Rohan Varma, Carnegie Mellon University 11:45-12:10 (25min) Déjeuner 12:10 - 14:00 (1h50) Déjeuner Excursion 14:00 - 20:00 (6h) Excursion	Bagging the Peaks: Matrix and Tensor Factorization with Unimodal Constraints 8:30 - 9:30 (1h) Bagging the Peaks: Matrix and Tensor Factorization with Unimodal Constraints A22 Amphi Wegener Urbashi Mitra https://sampta2019.sciencesconf.org/data/program/Mitra.pdf Pause café 9:30 - 10:00 (30min) Pause café Missing data imputation (invited) Echantillonage et analyse de Fourier 10:05 - 12:10 (2h05) Missing data imputation (invited) A9 Amphi 1 Laura Balzano & Rod Little › Comparison of Imputation Methods for Race and Ethnic Information in Administrative Health Data - Ofer Harel, University of Connecticut 10:05-10:30 (25min) › Adaptive sequential regression imputation methods using machine learning techniques - Trivellore E. Raghunathan, University of Michigan 10:30-10:55 (25min) › Tractable Learning of Sparsely Used Dictionaries from Incomplete Samples - 10:55-11:20 (25min) › Missing Data in Machine Learning - Laura Balzano, University of Michigan 11:20-11:35 (15min) › Missing Data in Classical Statistics - Rod Little, University of Michigan 11:35-11:50 (15min) › Discussion - Don Rubin, Harvard University 11:50-12:10 (20min) 10:05 - 12:10 (2h05) Echantillonage et analyse de Fourier A9 amphi 2 Ahmed Zayed › Sampling over spiraling curves - Felipe Negreira, Institut de Mathématiques de Bordeaux 10:05-10:30 (25min) › Time encoding and perfect recovery of non-bandlimited signals with an integrate-and-fire system - Roxana Alexandru, Imperial College London 10:30-10:55 (25min) › Optimal Spline Generators for Derivative Sampling - Shayan Aziznejad, EPFL 10:55-11:20 (25min) › On cosine operator function framework of windowed Shannon sampling operators - Andi Kivinukk, Tallinn University 11:20-11:45 (25min) › On Identifiability in Unlimited Sampling - Felix Krahmer, TU Munich 11:45-12:10 (25min) Déjeuner 12:10 - 13:45 (1h35) Déjeuner Lyapunov's theorem and sampling of continuous frames 13:45 - 14:45 (1h) Lyapunov's theorem and sampling of continuous frames A22 Amphi Wegener Marcin Bownik https://sampta2019.sciencesconf.org/data/program/Bownik_1.pdf Graph signal processing (invited) Wavelets, Shearlets… Super-Résolution 14:50 - 16:05 (1h15) Graph signal processing (invited) A9 Amphi 1 Karlheinz Gröchenig & Isaac Pesenson › Sampling and reconstruction of graph signals: An overview of recent graph signal processing results - António G. Marques, Universidad Rey Juan Carlos 14:50-15:15 (25min) › Iterative Chebyshev Polynomial Algorithm for Signal Denoising on Graphs - 15:15-15:40 (25min) › A non-commutative viewpoint on graph signal processing - Mahya Ghandehari, University of Delaware 15:40-16:05 (25min) 14:50 - 16:05 (1h15) Wavelets, Shearlets… A9 amphi 2 Andi Kivinukk › Higher-dimensional wavelets and the Douglas-Rachford algorithm - Jeffrey Hogan, University of Newcastle 14:50-15:15 (25min) › Analytic and directional wavelet packets - Valery Zheludev, Tel Aviv University 15:15-15:40 (25min) › Optimization in the construction of nearly cardinal and nearly symmetric wavelets - Neil Dizon, University of Newcastle 15:40-16:05 (25min) 14:50 - 16:05 (1h15) Super-Résolution A9 Amphi 3 Sinan Gunturk › The dual approach to non-negative super-resolution: impact on primal reconstruction accuracy - Bogdan Toader, Oxford University, The Alan Turing Institute 14:50-15:15 (25min) › Conditioning of restricted Fourier matrices and super-resolution of MUSIC - Wenjing Liao, Georgia Tech 15:15-15:40 (25min) › Iterative Discretization of Optimization Problems Related to Superresolution - Axel Flinth, Institut de Mathématiques de Toulouse UMR5219 15:40-16:05 (25min) Pause café 16:05 - 16:30 (25min) Pause café Graph signal processing (invited) Wavelets, Shearlets… Echantillonage et analyse de Fourier 16:30 - 18:10 (1h40) Graph signal processing (invited) A9 Amphi 1 Karlheinz Gröchenig & Isaac Pesenson › Clustering on Dynamic Graphs based on Total Variation - Peter Berger, TU Vienna 16:30-16:55 (25min) › Enabling Prediction via Multi-Layer Graph Inference and Sampling - Stefania Sardellitti, Sapienza University [Rome] 16:55-17:20 (25min) › Blue-Noise Sampling of Signals on Graphs - Alejandro Parada, University of Delaware 17:20-17:45 (25min) › Average sampling, average splines and Poincare inequality on combinatorial graphs - Isaac Pesenson, Temple University 17:45-18:10 (25min) 16:30 - 17:45 (1h15) Wavelets, Shearlets… A9 amphi 2 Andi Kivinukk › Analysis of shearlet coorbit spaces in arbitrary dimensions using coarse geometry - René Koch, RWTH Aachen University 16:30-16:55 (25min) › Trace Result of Shearlet Coorbit Spaces on Lines - Qaiser Jahan, Indian Institute of Technology Mandi 16:55-17:20 (25min) 16:30 - 17:45 (1h15) Echantillonage et analyse de Fourier A9 Amphi 3 Arash Amini › On the Reconstruction of a Class of Signals Bandlimited to a Disc - Ahmed Zayed, DePaul University, Chicago 16:30-16:55 (25min) › The Solvability Complexity Index of Sampling-based Hilbert Transform Approximations - Volker Pohl, TU Munich 16:55-17:20 (25min) › The Convolution Word is Tied to the Exponential Kernel Transforms. What is a Parallel Expression for the Other Transforms? - Abdul Jerri, Clarkson University 17:20-17:45 (25min) Diner de conférence au "Café du port" 19:30 - 23:00 (3h30) Diner de conférence au "Café du port"	Robust and efficient identification of neural networks 8:30 - 9:30 (1h) Robust and efficient identification of neural networks A22 Amphi Wegener Massimo Fornasier https://sampta2019.sciencesconf.org/data/program/Fornasier.pdf Pause café 9:30 - 10:00 (30min) Pause café Quantization (invited) Analyse de Fourier 10:00 - 12:05 (2h05) Quantization (invited) A22 Amphi Wegener Sjoerd Dirksen & Rayan Saab › Robust One-bit Compressed Sensing With Manifold Data - 10:00-10:25 (25min) › One-Bit Sensing of Low-Rank and Bisparse Matrices - Simon Foucart, Texas A&M 10:25-10:50 (25min) › Robust 1-Bit Compressed Sensing via Hinge Loss Minimization - Alexander Stollenwerk, TU Aachen 10:50-11:15 (25min) › High-performance quantization for spectral super-resolution - Sinan Gunturk, New York University 11:15-11:40 (25min) › On one-stage recovery for ΣΔ-quantized compressed sensing - Ozgur Yilmaz, University of British Columbia 11:40-12:05 (25min) 10:00 - 12:05 (2h05) Analyse de Fourier A22 Amphi Edison Jeff Hogan › Riesz bases of exponentials for partitions of intervals - 10:00-10:25 (25min) › Computability of the Fourier Transform and ZFC - 10:25-10:50 (25min) › Rearranged Fourier Series and Generalizations to Non-Commutative Groups - Armenak Petrosyan, Oak Ridge National Laboratory 10:50-11:15 (25min) › Deterministic guarantees for L1 -reconstruction: A large sieve approach with geometric flexibility - Michael Speckbacher, Institut de Mathématiques de Bordeaux 11:15-11:40 (25min) › A Clifford Construction of Multidimensional Prolate Spheroidal Wave Functions - Hamed Baghal Ghaffari, University of Newcastle 11:40-12:05 (25min) Déjeuner 12:05 - 13:30 (1h25) Déjeuner Deep Learning Problèmes inverses 13:30 - 14:20 (50min) Deep Learning A22 Amphi Wegener Radu Balan › Approximation in Lp(μ) with deep ReLU neural networks - Felix Voigtlaender, Katholische Universitat Eichstatt-Ingolstadt 13:30-13:55 (25min) › Modeling Global Dynamics from Local Snapshots with Deep Generative Neural Networks - Scott Gigante, Yale University 13:55-14:20 (25min) 13:30 - 14:20 (50min) Problèmes inverses A22 Amphi Edison Steven Casey › Convergence Rates for Hölder-Windows in Filtered Back Projection - Matthias Beckmann, University of Hambourg 13:30-13:55 (25min) › Dynamical Sampling with a Burst-like Forcing Term - Ilya Krishtal, Northern Illinois University 13:55-14:20 (25min) Learning from moments - Large-scale learning with the memory of a goldfish 14:30 - 15:35 (1h05) Learning from moments - Large-scale learning with the memory of a goldfish A22 Amphi Wegener Rémi Gribonval (and closing) https://sampta2019.sciencesconf.org/data/program/Gribonval.pdf

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