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⏲ Duration: 35 min 17 sec ✓ Published: 18-Aug-2021
Description: Date: 2021-04-21nnTitle: Fundamental limits of (S)GD on neural networksnnAbstract: We consider the learning paradigm consisting of training general neural networks (NN) with (S)GD. What is the class of functions that can be learned with this paradigm? How does it compare to known classes such as PAC and SQ? Is depth/overapametrization needed to learn certain classes? We show that SGD on NN is equivalent to PAC while GD on NN is equivalent to SQ, obtaining a separation between the classes learned
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