Constraint Classification for Multiclass Classification and Ranking
Har-Peled, Sariel, Roth, Dan, Zimak, Dav
–Neural Information Processing Systems
We present a meta-algorithm for learning in this framework that learns via a single linear classifier in high dimension. We discuss distribution independent as well as margin-based generalization bounds and present empirical and theoretical evidence showing that constraint classification benefits over existing methods of multiclass classification.
Neural Information Processing Systems
Dec-31-2003