Learning ABCs: Approximate Bijective Correspondence for isolating factors of variation with weak supervision
Learning ABCs: Approximate Bijective Correspondence for isolating factors of variation with weak supervision
Representational learning forms the backbone of most deep learning applications, and the value of a learned representation is intimately tied to its information content regarding different factors of variation. Finding good representations depends on the nature of supervision and the learning algorithm. We propose a novel algorithm that utilizes a …