In this lecture, we will take our first step outside binary classification towards more complex outputs. We will consider the case of multiclass classification – where the classifier has to choose from among a finite (and possibly small) number of inference outcomes.
Lecture and readings

Thomas G. Dietterich and Ghulum Bakiri, Solving Multiclass Learning Problems via ErrorCorrecting Output Codes, JAIR, 1995.

Erin L. Allwein, Robert E. Schapire, Yoram Singer, Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers, ICML 2000. (Slides from ICML 2010)

Koby Crammer and Yoram Singer, On the Algorithmic Implementation of Multiclass Kernelbased Vector Machines, JMLR 2001.