Paper Info
Title
Deep Linear Networks with Arbitrary Loss: All Local Minima Are Global.
Abstract
We consider deep linear networks with arbitrary differentiable loss. We provide a short and elementary proof of the following fact: all local minima are global minima if each hidden layer is wider than either the input or output layer.
Year
Venue
Field
2018
international conference on machine learning
Topology,Mathematical optimization,Elementary proof,Maxima and minima,Differentiable function,Artificial neural network,Mathematics
DocType
Citations 
PageRank 
Conference
10
0.53
References 
Authors
4
2
Name
Order
Citations
PageRank
Laurent, Thomas1747.43
James H. von Brecht2936.45