On Connected Sublevel Sets in Deep Learning
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We study sublevel sets of the loss function in training deep neural networks. For linearly independent data, we prove that every sublevel set of the loss is connected and unbounded. We then apply this result to prove similar properties on the loss surface of deep over-parameterized neural nets with piecewise linear activation functions.
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