SOTAVerified

PAC learning

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

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 221–230 of 289 papers

TitleStatusHype
Distribution-Independent PAC Learning of Halfspaces with Massart Noise—0
Query-driven PAC-Learning for Reasoning—0
Lower Bounds for Adversarially Robust PAC Learning—0
Private Hypothesis Selection—0
Regression EquilibriumCode0
Quantum hardness of learning shallow classical circuits—0
From PAC to Instance-Optimal Sample Complexity in the Plackett-Luce Model—0
Differentially Private Learning of Geometric Concepts—0
Crowdsourced PAC Learning under Classification Noise—0
Fast Hyperparameter Tuning using Bayesian Optimization with Directional Derivatives—0
Show:102550
← PrevPage 23 of 29Next →

No leaderboard results yet.