Refutably Probably Approximately Correct Learning.
Algorithmic Learning Theory, 4th International Workshop on Analogical and Inductive Inference, AII '94, 5th International Workshop on Algorithmic Learning Theory, ALT '94, Reinhardsbrunn Castle, Germany, October 10-15, 1994, Proceedings,
, pp.469-483
(1994), [peer-reviewed]
Event Date:
October 10-15, 1994
Abstract / 概要
We propose a notion of the refutably PAC learning, which formalizes the refutability of hypothesis spaces in the PAC learning model. Intuitively, the refutably PAC learning for a concept class F requires that the learning algorithm should refute F with high…