YAND defines optimization search directions via the equi-affine normal of level sets, proving invariance under volume-preserving affine maps and global convergence for smooth objectives.
Mirror descent and nonlinear projected subgradient methods.Operations Research Letters, 31(3):167–175, 2003
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Yau's Affine Normal Descent: Algorithmic Framework and Convergence Analysis
YAND defines optimization search directions via the equi-affine normal of level sets, proving invariance under volume-preserving affine maps and global convergence for smooth objectives.