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Exact Schur-Sylvester Dimensionality Reductions for Non-Smooth Stochastic Complexity and Manifold Sampling

arXiv cs.LG · 13h ago Cached

This paper presents exact dimensionality reductions using Schur complement and Sylvester's determinant identity to reduce computational complexity from O(N^3) to O(k^3+N^2k) per step for non-smooth NML estimation, achieving over 14,000x speedup while maintaining numerical precision.

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