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We consider deep linear networks with arbitrary convex differentiable loss.
Neural networks and principal component analysis: Learning from examples without local minima
Baldi, P. and Hornik, K · 1989
Earlier work this paper cites.
Complex-valued autoencoders
Baldi, P. and Lu, Z · 2012
Earlier work this paper cites.
Exact solutions to the nonlinear dynamics of learning in deep linear neural networks
Saxe, A. M., McClelland, J. L., and Ganguli, S · 2014
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Deep learning without poor local minima
Kawaguchi, K · 2016
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Identity matters in deep learning
Hardt, M. and Ma, T · 2017
Closest in time.
Depth creates no bad local minima
Lu, H. and Kawaguchi, K · 2017
Closest in time.
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