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Convergence Rate Analysis of SOAP with Arbitrary Orthogonal Projection Matrices
In this short note, we establish, for the first time, the convergence rate of SOAP, an efficient and popular matrix-based optimizer for training deep neural networks. Our analysis extends to a more general variant of SOAP that admits arbitrary orthogonal projection matrices and requires only that th
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