Anastasios Antoniadis

Competing Mutual Information Constraints with Stochastic Competition-Based Activations for Learning Diversified Representations

This work aims to address the long-established problem of learning diversified representations. To this end, we combine information-theoretic arguments with stochastic competition-based activations, namely Stochastic Local Winner-Takes-All (LWTA) units. In this context, we ditch the conventional dee…