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Topological Vanilla Transfer Learning
In this paper we investigate the connection of topological similarity between source and target tasks with the efficiency of vanilla transfer learning (i. e., transfer learning without retraining) between them.
Hypothesis classes with a unique persistence diagram are NOT nonuniformly learnable
The implicit role of a topological term in a loss function is to restrict the class of functions in which we are learning (the hypothesis class) to those with a specific topology.
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