Computational Harmonic Analysis in Data Science and Machine Learning
Videos from CMO Workshop
Rebecca Willett, University of Chicago
Monday Sep 16, 2024 09:00 - 10:00
Learning Low-rank Functions With Neural Networks
Bernhard Bodmann, University of Houston
Monday Sep 16, 2024 10:00 - 10:30
Sparse recovery for linear combinations of heat kernels on graphs
Jeremias Sulam, Johns Hopkins University
Monday Sep 16, 2024 11:00 - 11:30
What did my deep network learn?
Shuyang Ling, New York University Shanghai
Monday Sep 16, 2024 11:30 - 12:00
Beyond unconstrained features: Neural collapse for shallow neural networks with general data
Shizhou Xu, UC Davis
Monday Sep 16, 2024 15:00 - 15:30
Fair Data Representation for Machine Learning at the Pareto Frontier
Oscar Mickelin, Princeton University
Monday Sep 16, 2024 15:30 - 16:00
Fast expansion into harmonics on the unit disk and ball
Yuehaw Khoo, The University of Chicago
Monday Sep 16, 2024 16:30 - 17:00
Convex relaxations for physics simulations
Rayan Saab, University of California San Diego
Monday Sep 16, 2024 17:00 - 17:30
Compressing neural networks for faster inference: sparsity, quantization, and low-rank approximation
Rene Vidal, University of Pennsylvania
Tuesday Sep 17, 2024 09:00 - 10:00
Semantic Information and Matching Pursuit Algorithms for Explainable AI
Yunpeng Shi, UC Davis
Tuesday Sep 17, 2024 10:00 - 10:30
Fast and robust alignment of images in sliced Wasserstein distance
George Kevrekidis, Johns Hopkins University
Tuesday Sep 17, 2024 11:00 - 11:30
Conformal Disentanglement with Autoencoder Architectures
Hau-Tieng Wu, Duke University
Tuesday Sep 17, 2024 11:30 - 12:00
Manifold denosing
Rob Webber, University of California San Diego
Tuesday Sep 17, 2024 15:00 - 15:30
Robust, randomized preconditioning for kernel ridge regression
Alberto Bietti, NYU
Tuesday Sep 17, 2024 15:30 - 16:00
Transformers and Associative Memories
Sui Tang, University of California Santa Barbara
Tuesday Sep 17, 2024 16:30 - 17:00
Solving Estimation Problems of Dynamical Systems by Exploiting Low-Dimensional Structures
Dustin Mixon, The Ohio State University
Wednesday Sep 18, 2024 16:00 - 17:00
Bilipschitz invariants
Sue Parkinson, U Chicago
Wednesday Sep 18, 2024 17:30 - 18:00
Depth Separation of Neural Networks in Learning
Joe Kileel, UT Austin
Thursday Sep 19, 2024 10:00 - 10:30
Covering numbers of real algebraic varieties and applications to data science
Boris Landa, Yale University
Thursday Sep 19, 2024 12:00 - 12:30
Inferring the Noise Structure in Large Data Matrices for Adaptive Detection and Recovery of Low-Rank Signals
