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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
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
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
Optimization and Dynamical Systems: Variational, Hamiltonian, and Symplectic Perspectives
Presenter
- Michael Jordan
April 20, 2020
IPAM
New deep neural networks solving non-linear inverse problems
Presenter
- Matti Lassas
April 20, 2020
IPAM
Scaling Hamilton-Jacobi Reachability Analysis for Robotics: Multi-agent Systems to Real-time Computation
Presenter
- Somil Bansal
April 3, 2020
IPAM
Scalability for Hamilton-Jacobi Reachability Analysis: Decomposition, Warm-Start Initialization, and Model Reduction
Presenter
- Sylvia Herbert
April 3, 2020
IPAM
Probabilistic max-plus schemes for solving Hamilton-Jacobi-Bellman equations
Presenter
- Marianne Akian
April 3, 2020
IPAM
Attenuation of the curse of dimensionality in continuous-time nonlinear optimal feedback stabilization problems
Presenter
- Ivan Yegorov
April 2, 2020
IPAM