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Computational/Statistical Gaps for Learning Neural Networks
Presenter
- Adam Klivans
April 13, 2021
IMSI
Contributions to deep learning using a mathematical approach: improved model uncertainty, certified robust models, and faster training of Neural ODEs
Presenter
- Adam Oberman
October 5, 2020
IPAM
From an ODE to accelerated stochastic gradient descent: convergence rate and empirical results
Presenter
- Adam Oberman
May 7, 2020
SLMath
Gradient descent, Stochastic gradient descent, and acceleration
Presenter
- Adam Oberman
March 10, 2020
IPAM
An ICERM Public Lecture - Bias in bios: fairness in a high-stakes machine-learning setting
Presenter
- Adam Kalai
March 21, 2019
ICERM
Learning Discrete Markov Random Fields with Nearly Optimal Runtime and Sample Complexity
Presenter
- Adam Klivans
March 20, 2019
ICERM
Partial Differential Equations Approaches to Optimization and Regularization of Deep Neural Networks
Presenter
- Adam Oberman
November 2, 2018
ICERM
Spatiotemporal modelling of ocean surface velocities from drifters
Presenter
- Adam Sykulski
April 24, 2018
IMA
Using Brownian Motion Processes to Compute the Electroneutral Limit of Electrodiffusion
Presenter
- Adam Stinchcombe
March 14, 2018
IMA