PROGRAM
Plenary Speakers
- Luis Daniel Abreu (Acoustics Research Institute Vienna)
- "Time-frequency analysis: from the plane to the flat torus. Deterministic and random aspects"
- Akram Aldroubi (Vanderbilt University)
- "Optimal transport transforms in signal processing and data science"
- Rima Alaifari (ETH Zürich)
- "Recent advances in phase retrieval"
- Afonso Bandeira (ETH Zürich)
- "Computation, statistics, and optimization of random functions"
- Mikhail Belkin (University of California, San Diego)
- "The mathematical challenges of modern machine learning"
- Helmut Boelcskei (ETH Zürich)
- "Fundamental limits of generative deep neural networks"
- Annie Cuyt (University of Antwerp)
- "Exponential analysis: solving open problems and unlocking new potential"
- Mark Iwen (Michigan State University)
- "Generalized sparse Fourier transforms for approximating functions of many variables"
- Hrushikesh Mhaskar (Claremont Graduate University)
- "Super-resolution meets machine learning"
- Dustin Mixon (Ohio State University)
- "Optimal projective codes"
- Justin Romberg (Georgia Institute of Technology)
- "Distributed stochastic approximation: reinforcement learning and optimization with communication constraints"
- Karin Schnass (University of Innsbruck)
- "A peek at the landscape of dictionary learning"
- Joel Tropp (California Institute of Technology)
- "Scalable semidefinite programming"