On the learnability of discrete distributions 论文
1994引用 285
Machine Learning and AlgorithmsAlgorithms and Data CompressionMachine Learning and Data Classification
摘要
We introduce and investigate a new model of learning probability distributions from independent draws. Our model is inspired by the popular Probably Approximately Correct (PAC) model for learning boolean functions from labeled