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Is non-convex optimization really hard? A couple of recent stories
Presenter
- Emmanuel Candès
September 26, 2018
IPAM
Misha Belkin - The elusive generalization and easy optimization, Pt. 1 of 2 - IPAM at UCLA
Presenter
- Misha Belkin
September 12, 2024
IPAM
Misha Belkin - The elusive generalization and easy optimization, Pt. 2 of 2 - IPAM at UCLA
Presenter
- Misha Belkin
September 12, 2024
IPAM
Equivariant machine learning, structure like classical physics
Presenter
- Soledad Villar
March 4, 2022
IMSI
Machine learning-assisted ensemble calculations of the physical properties of disordered colloidal composites
Presenter
- Rob Coridan
March 3, 2022
IMSI
Establishing trust in decisions made from data: Physics-informed machine-learning models with computable generalization bounds
Presenter
- Benjamin Peherstorfer
March 2, 2022
IMSI
A three-pronged approach to using machine learning in knot theory
Presenter
- Mark Hughes
May 24, 2023
ICERM
Multiscale analysis of accelerated gradient methods in machine learning
Presenter
- Mohammad Farazmand
October 28, 2019
IPAM
Learning dynamics with dynamical distances: From diffusion maps to commute maps and coherence
Presenter
- Ralf Banisch
December 5, 2016
IPAM
Momentum in Stochastic Gradient Descent and Deep Neural Nets
Presenter
- Bao Wang
January 29, 2020
IPAM