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Isaac Newton Institute Seminar Series
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The Isaac Newton Institute for Mathematical Sciences is a national and international visitor research institute. It runs research programmes on selected themes in mathematics and the mathematical sciences with applications over a wide range of science and technology. You can receive regular information by email on Institute seminars and events by subscribing to our mailing lists: follow the instructions at http://www.newton.cam.ac.uk/mailing.html. There are lists for each individual Institute programme. If you have a question about this list, please contact: Jonathan H N Chin; Chie Sibley Obata; Kathryn de Ridder; Clare Merritt; info@newton.ac.uk; Vincenzo Abete; ss917; ad864. If you have a question about a specific talk, click on that talk to find its organiser. 48 upcoming talks and 9574 talks in the archive: show first 500. Dynamical sampling and frames generated from powers of exponential operatorsASCW03 - Approximation, sampling, and compression in high dimensional problems
Dynamical sampling and frames generated from powers of exponential operatorsASCW03 - Approximation, sampling, and compression in high dimensional problems
Transportation cost spaces on finite metric spacesASCW03 - Approximation, sampling, and compression in high dimensional problems
Transportation cost spaces on finite metric spacesASCW03 - Approximation, sampling, and compression in high dimensional problems
Optimal sampling for approximation on general domainsASCW03 - Approximation, sampling, and compression in high dimensional problems
Optimal sampling for approximation on general domainsASCW03 - Approximation, sampling, and compression in high dimensional problems
High Dimensional Approximation via Sparse Occupancy TreesASCW03 - Approximation, sampling, and compression in high dimensional problems
High Dimensional Approximation via Sparse Occupancy TreesASCW03 - Approximation, sampling, and compression in high dimensional problems
Representer theorems and convex optimizationASCW03 - Approximation, sampling, and compression in high dimensional problems
Representer theorems and convex optimizationASCW03 - Approximation, sampling, and compression in high dimensional problems
Functions of Few Coordinate Variables: Sampling Schemes and Recovery AlgorithmsASCW03 - Approximation, sampling, and compression in high dimensional problems
Functions of Few Coordinate Variables: Sampling Schemes and Recovery AlgorithmsASCW03 - Approximation, sampling, and compression in high dimensional problems
Discrete translates in function spacesASCW03 - Approximation, sampling, and compression in high dimensional problems
Discrete translates in function spacesASCW03 - Approximation, sampling, and compression in high dimensional problems
Optimal algorithms for state estimation using reduced modelsASCW03 - Approximation, sampling, and compression in high dimensional problems
Optimal algorithms for state estimation using reduced modelsASCW03 - Approximation, sampling, and compression in high dimensional problems
A sequence of well-conditioned polynomialsASCW03 - Approximation, sampling, and compression in high dimensional problems
A sequence of well-conditioned polynomialsASCW03 - Approximation, sampling, and compression in high dimensional problems
Linear and one-bit compressive sensing with subsampled random convolutionsASCW03 - Approximation, sampling, and compression in high dimensional problems
Linear and one-bit compressive sensing with subsampled random convolutionsASCW03 - Approximation, sampling, and compression in high dimensional problems
Quasi-Monte Carlo integration in uncertainty quantification of elliptic PDEs with log-Gaussian coefficientsASCW03 - Approximation, sampling, and compression in high dimensional problems
Quasi-Monte Carlo integration in uncertainty quantification of elliptic PDEs with log-Gaussian coefficientsASCW03 - Approximation, sampling, and compression in high dimensional problems
Basis properties of the Haar system in various function spacesASCW03 - Approximation, sampling, and compression in high dimensional problems
Basis properties of the Haar system in various function spacesASCW03 - Approximation, sampling, and compression in high dimensional problems
On singular Brascamp Lieb integralsASCW03 - Approximation, sampling, and compression in high dimensional problems
On singular Brascamp Lieb integralsASCW03 - Approximation, sampling, and compression in high dimensional problems
Approximation of continuous problems in Fourier Analysis by finite dimensional ones: The setting of the Banach Gelfand TripleASCW03 - Approximation, sampling, and compression in high dimensional problems
Approximation of continuous problems in Fourier Analysis by finite dimensional ones: The setting of the Banach Gelfand TripleASCW03 - Approximation, sampling, and compression in high dimensional problems
Extracting bits from analog samples: in pursuit of optimalityASCW03 - Approximation, sampling, and compression in high dimensional problems
Extracting bits from analog samples: in pursuit of optimalityASCW03 - Approximation, sampling, and compression in high dimensional problems
Stochastic Quasi-Gradient Methods: Variance Reduction via Jacobian SketchingASCW03 - Approximation, sampling, and compression in high dimensional problems
Stochastic Quasi-Gradient Methods: Variance Reduction via Jacobian SketchingASCW03 - Approximation, sampling, and compression in high dimensional problems
On some theorems on the restriction of operator to coordinate subspaceASCW03 - Approximation, sampling, and compression in high dimensional problems
On some theorems on the restriction of operator to coordinate subspaceASCW03 - Approximation, sampling, and compression in high dimensional problems
Orthogonal structure in and on quadratic surfacesASCW03 - Approximation, sampling, and compression in high dimensional problems
Orthogonal structure in and on quadratic surfacesASCW03 - Approximation, sampling, and compression in high dimensional problems
Beating the Curse of Dimensionality: A Theoretical Analysis of Deep Neural Networks and Parametric PDEsASCW03 - Approximation, sampling, and compression in high dimensional problems
Beating the Curse of Dimensionality: A Theoretical Analysis of Deep Neural Networks and Parametric PDEsASCW03 - Approximation, sampling, and compression in high dimensional problems
How good is random information compared to optimal information?ASCW03 - Approximation, sampling, and compression in high dimensional problems
How good is random information compared to optimal information?ASCW03 - Approximation, sampling, and compression in high dimensional problems
Totally positive functions in sampling theory and time-frequency analysisASCW03 - Approximation, sampling, and compression in high dimensional problems
Totally positive functions in sampling theory and time-frequency analysisASCW03 - Approximation, sampling, and compression in high dimensional problems
Integral norm discretization and related problemsASCW03 - Approximation, sampling, and compression in high dimensional problems
Integral norm discretization and related problemsASCW03 - Approximation, sampling, and compression in high dimensional problems
Imaging through optical fibresASCW03 - Approximation, sampling, and compression in high dimensional problems
Imaging through optical fibresASCW03 - Approximation, sampling, and compression in high dimensional problems
Markov-type inequalities and extreme zeros of orthogonal polynomialsASCW03 - Approximation, sampling, and compression in high dimensional problems
Markov-type inequalities and extreme zeros of orthogonal polynomialsASCW03 - Approximation, sampling, and compression in high dimensional problems
Please see above for contact details for this list. |
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Akram Aldroubi (Vanderbilt University; Vanderbilt University).
Monday 17 June 2019, 09:50-10:40