Method for training a learning machine having a deep multi-layered network with labeled and unlabeled training data
US8234228B2 · kind B2 · utility
22Cited by
1References
12Claims
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Key dates
| Filing date | Feb 6, 2009 |
| Grant date | Jul 31, 2012 |
| Priority date | — |
| Expiry date | Dec 27, 2030 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/09
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The invention includes a method for training a learning machine having a deep multi-layered network, with labeled and unlabeled training data. The deep multi-layered network is a network having multiple layers of non-linear mapping. The method generally includes applying unsupervised embedding to any one or more of the layers of the deep network. The unsupervised embedding is operative as a semi-supervised regularizer in the deep network.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.