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Orthogonality constraints in machine learning are hard to scale. A new method optimizes orthogonal matrices in a simpler way. This could make robust and probabilistic machine learning more efficient.
“arXiv:2602.14656v2 Announce Type: replace Abstract: Orthogonality constraints are ubiquitous in robust and probabilistic machine learning. Unfortunately, current optimizers are computationally expensive and do not scale to problems with hun…”
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arXiv:2602.14656v2
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Aug 7, 2026