New architectures for very deep learning
- Srivastava, Rupesh Kumar
- Schmidhuber, Jürgen (degree supervisor)
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01.02.2018
116 p
Thèse de doctorat: Università della Svizzera italiana, 2018
Machine learning
Deep learning
Very deep learning
Neural networks
Highway networks
Local competition
Competitive learning
English
Artificial Neural Networks are increasingly being used in complex real- world applications because many-layered (i.e., deep) architectures can now be trained on large quantities of data. However, training even deeper, and therefore more powerful networks, has hit a barrier due to fundamental limitations in the design of existing networks. This thesis develops new architectures that, for... Show more…
- Language
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- English
- Classification
- Computer science
- License
- License undefined
- Identifiers
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- RERO DOC 322586
- URN urn:nbn:ch:rero-006-117364
- Persistent URL
- https://susi.usi.ch/usi/documents/318812