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Arxiv
1d
42
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An extrapolated and provably convergent algorithm for nonlinear matrix decomposition with the ReLU function
- Nonlinear matrix decomposition with the ReLU function finds application in various fields.
- The standard ReLU-NMD model minimizes the least squares error while the Latent-ReLU-NMD model introduces a latent variable to achieve a different low-rank solution.
- The 3B-ReLU-NMD model allows elimination of the rank constraint in Latent-ReLU-NMD.
- A novel extrapolated variant, eBCD-NMD, of block coordinate descent (BCD) for 3B-ReLU-NMD is proven to be convergent and offers significant acceleration.
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