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Toward a theory of optimization for over-parameterized systems of non-linear equations: the lessons of deep learning
Presenter
- Mikhail Belkin
April 21, 2020
IPAM
Assumption-free prediction intervals for black-box regression algorithms
Presenter
- Aaditya Ramdas
April 21, 2020
IAS
A mean-field theory of lazy training in two-layer neural nets: entropic regularization and controlled McKean-Vlasov dynamics
Presenter
- Maxim Raginsky
April 21, 2020
IPAM
Non-commutative optimization: theory, algorithms and applications (or, can we prove P!=NP using gradient descent)
Presenter
- Avi Wigderson
April 21, 2020
IAS
Understanding and mitigating gradient flow pathologies in physics-informed neural networks
Presenter
- Paris Perdikaris
April 21, 2020
ICERM
Active learning and experimental design - who should we test?
Presenter
- Eldad Haber
April 21, 2020
IPAM
Projected Stein variational methods for high-dimensional Bayesian inversion constrained by large-scale PDEs
Presenter
- Peng Chen
April 21, 2020
IPAM
A Lyapunov analysis for accelerated gradient methods: From deterministic to stochastic case
Presenter
- Maxime Laborde
April 20, 2020
IPAM
From Fourier to Koopman - Spectral Methods for Long-term Time Series Prediction
Presenter
- J. Nathan Kutz
April 20, 2020
ICERM
Optimization and Dynamical Systems: Variational, Hamiltonian, and Symplectic Perspectives
Presenter
- Michael Jordan
April 20, 2020
IPAM