Research map / Optimization / Implicit bias and generalization
A global convergence theory for deep ReLU implicit networks via over-parameterization
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| increase width m | ReLU implicit neural network trained by gradient descent · MNIST, FashionMNIST, CIFAR10, and SVHN (binary-class subsets) | training loss | Helped |
| increase width m | ReLU implicit neural network trained by gradient descent · MNIST, FashionMNIST, CIFAR10, and SVHN (binary-class subsets) | test loss | Helped |
| increase width m | ReLU implicit neural network trained by gradient descent · MNIST, FashionMNIST, CIFAR10, and SVHN (binary-class subsets) | operator norm of scaled A | Mixed |
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