NS-RGS uses Newton-Schulz iterations to avoid costly matrix decompositions in Riemannian optimization for orthogonal group synchronization, proving linear convergence with spectral initialization and showing 2x practical speedup.
Viewing direction estimation in cryo-em using synchronization.SIAM J
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NS-RGS: Newton-Schulz based Riemannian gradient method for orthogonal group synchronization
NS-RGS uses Newton-Schulz iterations to avoid costly matrix decompositions in Riemannian optimization for orthogonal group synchronization, proving linear convergence with spectral initialization and showing 2x practical speedup.