Online Supervised Dimension Reduction with Random Features: Diagnostics and Computational Trade-offs
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arXiv:2609.20454v1 Announce Type: new Abstract: Accurate optimization of a supervised spectral objective need not produce an accurate population subspace or a better predictive representation. We investigate these distinctions for Online Kernel Supervised Principal Component Analysis (OKSPCA), whic…
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- 2026-09-18 04:00 · arXiv stat.ML
Online Supervised Dimension Reduction with Random Features: Diagnostics and Computational Trade-offs