The Probably Approximately Correct Learning Model in Computational Learning Theory
arXiv:2511.08791v12 citations
Originality Synthesis-oriented
AI Analysis
It synthesizes foundational concepts in computational learning theory for researchers, but is incremental as it reviews prior work.
This survey paper provides an overview of known results on learning Boolean functions in the Probably Approximately Correct (PAC) learning model and its variants, summarizing existing research without presenting new experimental outcomes.
This survey paper gives an overview of various known results on learning classes of Boolean functions in Valiant's Probably Approximately Correct (PAC) learning model and its commonly studied variants.