Decentralized Principal Component Analysis by Integrating Lagrange Programming Neural Networks With Alternating Direction Method of Multipliers
Conventional centralized methods use entire data to estimate the projection matrix of dimensionality reduction problem, which are not suitable for the network environment where the sensitive or private data are stored or there is no fusion center. In this paper, we develop a decentralized principal...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9218987/ |