Sparse Priors for Efficient Distribution Learning
arXiv:2609.20883v1 Announce Type: new Abstract: Despite the widespread use and success of generative AI techniques today, theoretical guarantees on learning a distribution supported in $d$ dimensions from $n$ samples degrade as $O(n^{-1/\Theta(d)})$, though shown to be minimax optimal. We hypothesi…
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- 2026-09-21 04:00 · arXiv cs.LG
Sparse Priors for Efficient Distribution Learning