AI RESEARCH
PRIM-cipal components analysis
arXiv CS.LG
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ArXi:2604.15538v1 Announce Type: cross Supervised No Free Lunch Theorems (NFLTs) are well studied, yet unsupervised NFLTs remain underexplored. For elliptical distributions, we prove that there exist two equally optimal, scientifically meaningful bump-hunting strategies that are exact opposites, with no universal winner.