Loss landscapes and optimization in over-parameterized non-linear systems and neural networks

Author:

Liu ChaoyueORCID,Zhu Libin,Belkin Mikhail

Funder

National Science Foundation

Simons Foundation

NSF

Google

Publisher

Elsevier BV

Subject

Applied Mathematics

Reference38 articles.

1. A convergence theory for deep learning via over-parameterization;Allen-Zhu,2019

2. Fine-grained analysis of optimization and generalization for overparameterized two-layer neural networks;Arora,2019

3. Gradient descent with identity initialization efficiently learns positive-definite linear transformations by deep residual networks;Bartlett;Neural Comput.,2019

4. Reconciling modern machine- learning practice and the classical bias-variance trade-off;Belkin;Proc. Natl. Acad. Sci.,2019

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