No Free Lunch Theorem

Thu, 09 Jul 2026 21:02:56 +1000

averaged over all possible problems, every learning algorithm is exactly as good as random guessing — and every optimiser is exactly as good as blind enumeration. 𐃏 this sounds like nihilism but is actually the sharpest possible argument for inductive bias: an algorithm can only beat chance on some problems by losing to chance on others, so the whole game of machine learning is choosing whose lunch to eat.

No-Free-Lunch on Aayush Bajaj's Augmenting Infrastructure

No Free Lunch Theorem