Gradient Descent Aligns The Layers Of Deep Linear Networks
Gradient Descent Aligns The Layers Of Deep Linear Networks. Specifically, for each layer, the ratio of spectral to frobenius norms is plotted, and converges to. Upload an image to customize your repository’s social media preview.
By ziwei ji and matus telgarsky. Images should be at least 640×320px (1280×640px for best display). This paper establishes risk convergence and asymptotic weight matrix.
Upload An Image To Customize Your Repository’s Social Media Preview.
By ziwei ji and matus telgarsky. Gradient descent aligns the layers of deep linear networks. Images should be at least 640×320px (1280×640px for best display).
Specifically, For Each Layer, The Ratio Of Spectral To Frobenius Norms Is Plotted, And Converges To.
This paper establishes risk convergence and asymptotic weight matrix. Get pdf (648 kb) abstract.