Mirror flow reaches max-margin solutions in homogeneous neural networks where the mirror map choice controls whether learned features are sparse or dense while convergence can be exponentially slow.
Learning multiple layers of features from tiny images
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Implicit Bias of Mirror Flow in Homogeneous Neural Networks: Sparse and Dense Feature Learning
Mirror flow reaches max-margin solutions in homogeneous neural networks where the mirror map choice controls whether learned features are sparse or dense while convergence can be exponentially slow.