Troels C. Petersen

Multiclass Classification without Labels via Posterior Simplex Geometry

Classification without Labels (CWoLa) shows that, in the binary case, a classifier trained to distinguish two impure mixtures with different class proportions can recover an optimal class discriminator without knowing the mixture proportions, and proposes prior-free procedures that train a standard classifier to distinguish mixture identities and then extract latent class structure using either post-hoc simplex fitting or a bottleneck architecture.