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cs.LG2022
Finite Sample Identification of Wide Shallow Neural Networks with Biases
Massimo Fornasier, Timo Klock, Marco Mondelli +1
Artificial neural networks are functions depending on a finite number of parameters typically encoded as weights and biases. The identification of the parameters of the network fro…
cs.LG2022★ 3 cited
Semi-Supervised Manifold Learning with Complexity Decoupled Chart Autoencoders
Stefan C. Schonsheck, Scott Mahan, Timo Klock +2
Autoencoding is a popular method in representation learning. Conventional autoencoders employ symmetric encoding-decoding procedures and a simple Euclidean latent space to detect h…