Sep 29, 2018 · In this paper, we provide such an analysis on the simple problem of ordinary least squares (OLS). Since precise dynamical properties of gradient ...
May 9, 2019 · A Quantitative Analysis of the Effect of Batch Normalization on Gradient Descent. Figure 5. The geometric meaning of the separation property.
Here the normalizing matrices Si,i = 1, ..., m, are assumed to be positive definite and Si does not depend on wi and γi. (it could depend on wj or γj,j < i) ...
Despite its empirical success and recent theoretical progress, there generally lacks a quantitative analysis of the effect of batch normalization (BN) on ...
It is shown that unlike GD, gradient descent with BN (BNGD) converges for arbitrary learning rates for the weights, and the convergence remains linear under ...
Batch normalization works well in practice, e.g. allows stable training with large learning rates, works well in high dimensions or ...
A quantitative analysis of the effect of batch normalization on gradient descent ... Analytical calculation of the elastic moduli of self-assembled liquid ...
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In this work, we investigate the quantitative effect of applying batch normalization to simplified machine learning problems. In this case, we can prove ...
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A Quantitative Analysis of the Effect of Batch Normalization on Gradient Descent ... Well-posedness of the limiting equation of a noisy consensus model in ...