$(\alpha,\beta)$-Stability for Boosting Vector-Valued Prediction

ArXi:2602.18866v2 Announce Type: replace Despite the widespread use of boosting in structured prediction, a general theoretical understanding of aggregation beyond scalar prediction remains incomplete. We study vector-valued prediction under a target divergence and identify a geometric stability property under which aggregation amplifies weak guarantees into strong ones. We formalize this property as $(\alpha,\beta)$-stability by geometric median and show how it s a boosting framework based on exponential reweighting and geometric-median aggregation.