The ultrametric organization of memories in a neural network

N. Parga , M.A. Virasoro

In the original formulation of Hopfield's memory model, the learning rule setting the interaction strengths is best suited for orthogonal words. From the point of view of categorization, this feature is not convenient unless we reinterpret these words as primordial categories. But then one has to complete the model so as to be able to store a full hierarchical tree of categories embodying subcategories and so on. We use recent results on the spin glass mean field theories to show that this completion can be done in a natural way with a minimal modification of Hebb's rule for learning. Categorization emerges naturally from an encoding stage structured in layers.

Mots clés: neural nets

Domaines: Articles anciens

N. Parga, M.A. Virasoro. The ultrametric organization of memories in a neural network. Journal de Physique, 1986, 47 (11), pp.1857-1864. ⟨10.1051/jphys:0198600470110185700⟩. ⟨jpa-00210382⟩