Unsupervised learning of invariant representations
The present phase of Machine Learning is characterized by supervised learning algorithms relying on large sets of labeled examples (n → ∞). The next phase is likely to focus on algorithms capable of learning from very few labeled examples (n → 1), like humans seem able to do. We propose an approach...
| Main Authors: | , , , , , |
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| Other Authors: | , |
| Format: | Article |
| Language: | English |
| Published: |
Elsevier,
2018-06-06T14:01:56Z.
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| Subjects: | |
| Online Access: | Get fulltext |