Justinas Zaliaduonis

The Loss Is Not Enough: Sampling Conditions and Inductive Bias in Contrastive Representation Learning

Contrastive learning has emerged as a powerful paradigm for self-supervised representation learning, yet the precise conditions under which it recovers meaningful latent structure remain incompletely understood. We develop a measure-theoretic framework that formalizes the diversity condition, a requ…