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PAC learning

Probably Approximately Correct (PAC) learning analyzes machine learning mathematically using probability bounds.

Papers

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Showing 201–210 of 289 papers

TitleStatusHype
PAC Learning Linear Thresholds from Label Proportions—0
PAC-Learning Uniform Ergodic Communicative Networks—0
PAC Learning, VC Dimension, and the Arithmetic Hierarchy—0
PAC Learning with Improvements—0
PAC learning with nasty noise—0
PAC learning with stable and private predictions—0
PAC Verification of Statistical Algorithms—0
Private Hypothesis Selection—0
A Characterization of Multiclass Learnability—0
A Characterization of Semi-Supervised Adversarially-Robust PAC Learnability—0
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