Geometric Properties of Learned Representations
In machine learning, reprensentation learning refers to optimizing a mapping from data to some representation space (usually generic vectors in Rᵈ for some pre-determined 𝑑 much lower than data dimensions). While such training often uses no supervised labels, the learned representations have proved...
Main Author: | Wang, Tongzhou |
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Other Authors: | Isola, Phillip |
Format: | Thesis |
Published: |
Massachusetts Institute of Technology
2023
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Online Access: | https://hdl.handle.net/1721.1/147353 |
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