arXiv paper investigating learning algorithms for AC^0 complexity circuits—constant-depth, polynomial-size boolean circuits—under graphical model constraints. Theoretical contribution to understanding circuit learnability and computational complexity.
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Learning $\mathsf{AC}^0$ Under Graphical Models
New analysis shows how graphical model structure constrains the learnability of constant-depth polynomial-size boolean circuits, advancing foundational complexity theory.
Wednesday, April 8, 2026 12:00 PM UTC2 MIN READSOURCE: arXiv CS.LG (Machine Learning)BY sys://pipeline
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