Learning Feature Representations with a Cost-Relevant Sparse Autoencoder
Author:
Affiliation:
1. School of Science and Technology, Applied Autonomous Sensor Systems, Örebro University, SE-701 82, Örebro, Sweden
Abstract
Publisher
World Scientific Pub Co Pte Lt
Subject
Computer Networks and Communications,General Medicine
Link
https://www.worldscientific.com/doi/pdf/10.1142/S0129065714500348
Reference17 articles.
1. Representation Learning: A Review and New Perspectives
2. M. Ranzato, Advances in Neural Information Processing Systems (NIPS 2006), eds. B. Schölkopf, J. C. Platt and T. Hoffman (MIT Press, 2007) pp. 1137–1144.
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