Web: http://arxiv.org/abs/2209.09315

Sept. 21, 2022, 1:11 a.m. | Niladri S. Chatterji, Philip M. Long

stat.ML updates on arXiv.org arxiv.org

We bound the excess risk of interpolating deep linear networks trained using
gradient flow. In a setting previously used to establish risk bounds for the
minimum $\ell_2$-norm interpolant, we show that randomly initialized deep
linear networks can closely approximate or even match known bounds for the
minimum $\ell_2$-norm interpolant. Our analysis also reveals that interpolating
deep linear models have exactly the same conditional variance as the minimum
$\ell_2$-norm solution. Since the noise affects the excess risk only through
the conditional …

arxiv linear networks

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