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Intro
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Classroom Contents
Beyond Lazy Training for Over-parameterized Tensor Decomposition
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- 1 Intro
- 2 Low rank models and implicit regularizati
- 3 Regimes of over-parametrization
- 4 Tensor (CP) decomposition
- 5 Why naïve algorithm fails
- 6 Why gradient descent?
- 7 Two-Layer Neural Network
- 8 Form of the objective
- 9 Difficulties of analyzing gradient descent
- 10 Lazy training fails
- 11 O is a high order saddle point
- 12 There are local minima away from 0
- 13 Our (high level) algorithm
- 14 Proof ideas
- 15 Escaping local minima by random correla
- 16 Amplify initial correlation by tensor power man
- 17 Conclusions and Open Problems
