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: | en_US |
| Published: |
Elsevier
2018
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| Online Access: | http://hdl.handle.net/1721.1/116137 https://orcid.org/0000-0002-0264-4761 https://orcid.org/0000-0002-3153-916X https://orcid.org/0000-0001-6376-4786 https://orcid.org/0000-0001-6130-5631 https://orcid.org/0000-0001-9311-9171 https://orcid.org/0000-0002-3944-0455 |