Defensive Boosting for Online Probabilistic Forecasting

By Georgy Noarov · Paper · cs.LG

We study online probabilistic forecasting of binary outcomes chosen by an adaptive adversary. Given an online learning algorithm for a weak hypothesis class $H$, we would like to efficiently obtain two incomparable guarantees that existing online boosting techniques provide separ

Cs.lg

View original

HomeResourceLoading…