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Non-Vacuous Generalisation Bounds for Shallow Neural Networks

ICML 2022 · Optimization › Implicit bias and generalization · approach: Shallow ReLU network convergence · 1 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use a coupled prior trained on a prefix of the training data instead of a full-data-independent priorSHEL with momentum SGD · Bin-Mgeneralisation bound: 0.837 -> 0.286Helped
Use a coupled prior trained on a prefix of the training data instead of a full-data-independent priorSHEL with momentum SGD · Bin-Fgeneralisation bound: 0.426 -> 0.297Helped
Use a coupled prior trained on a prefix of the training data instead of a full-data-independent priorSHEL with momentum SGD · MNISTgeneralisation bound: 0.772 -> 0.490Helped
Use a coupled prior trained on a prefix of the training data instead of a full-data-independent priorSHEL with momentum SGD · Fashion-MNISTgeneralisation bound: 0.984 -> 0.727Helped
Use a coupled prior trained on a prefix of the training data instead of a full-data-independent priorGELU with momentum SGD · MNISTgeneralisation bound: 0.693 -> 0.293Helped
Use a coupled prior trained on a prefix of the training data instead of a full-data-independent priorGELU with momentum SGD · Fashion-MNISTgeneralisation bound: 0.976 -> 0.568Helped
Use a coupled prior trained on a prefix of the training data instead of a full-data-independent priorSHEL without momentum SGD · Bin-Mgeneralisation bound: 0.835 -> 0.286Helped
Use a coupled prior trained on a prefix of the training data instead of a full-data-independent priorSHEL without momentum SGD · Bin-Fgeneralisation bound: 0.425 -> 0.300Helped
Use a coupled prior trained on a prefix of the training data instead of a full-data-independent priorSHEL without momentum SGD · MNISTgeneralisation bound: 0.821 -> 0.522Helped
Use a coupled prior trained on a prefix of the training data instead of a full-data-independent priorSHEL without momentum SGD · Fashion-MNISTgeneralisation bound: 1.109 -> 0.844Helped
Use a coupled prior trained on a prefix of the training data instead of a full-data-independent priorGELU without momentum SGD · MNISTgeneralisation bound: 0.742 -> 0.317Helped
Use a coupled prior trained on a prefix of the training data instead of a full-data-independent priorGELU without momentum SGD · Fashion-MNISTgeneralisation bound: 1.100 -> 0.709Helped

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