Videos

Practical existence theorems for deep learning approximation in high dimensions

BIRS workshop, Structured Machine Learning and Time–Stepping for Dynamical Systems (24w5301)

Banff International Research Station (BIRS) for Mathematical Innovation and Discovery. Banff, AB, Canada. February 19, 2024.

Link (for full-screen vision): https://www.birs.ca/events/2024/5-day-workshops/24w5301/videos/watch/202402191611-Brugiapaglia.html

The mathematical foundations of deep learning: from rating impossibility to practical existence theorems

One World Seminar Series on the Mathematics of Machine Learning

Online. November 16, 2022.

The curse of dimensionality and the blessings of sparsity and Monte Carlo sampling

One World Mathematics of INformation, Data, and Signals (1W-MINDS) Seminar

Online. May 13, 2021.

Compressive Sensing Approaches for High-Dimensional Function Approximation

DASIV Spring School Models and Data.

University of South Carolina. Columbia, SC, USA. March 20, 2019.

Sparse High-dimensional Approximation from Highly Noisy Data

BIRS workshop, 18w5172: Numerical Analysis and Approximation Theory meets Data Science

Banff International Research Station (BIRS) for Mathematical Innovation and Discovery. Banff, AB, Canada. April 22, 2018.

Link (for full-screen vision): https://www.birs.ca/events/2018/5-day-workshops/18w5172/videos/watch/201804231118-Brugiapaglia.html

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