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DCA's convergence rate and behavior are highly dependent on the specific DC decomposition used, offering a geometric criterion for assessing decomposition quality and linking DCA with Bregman geometry.
Escape the tyranny of ill-conditioned optimization landscapes: Yau's Affine Normal Descent offers provably robust convergence by intrinsically adapting to anisotropic curvature through volume-preserving affine invariance.