Barlow’s redundancy-reduction principle applied to a pair of identical networks. The objective function measures the cross-correlation matrix between the output features of two identical networks fed with distorted versions of a batch of samples and attempts to bring this matrix close to the identity. This causes the representation vectors of distorted versions of a sample to be similar, while minimizing the redundancy between the components of these vectors (Figure 7).
Les vecteurs de représentation des versions déformées d’un échantillon sont ainsi similaires, tout en minimisant la redondance entre les composantes de ces vecteurs (figure 7).