193 citations · 502 across the 17 of their papers we have counts for
3 papers · 1 filter
Measuring group-separability in geometrical space for evaluation of pattern recognition and embedding algorithms
A. Acevedo, S. Ciucci, MJ. Kuo +2
Evaluating data separation in a geometrical space is fundamental for pattern recognition. A plethora of dimensionality reduction (DR) algorithms have been developed in order to rev…
Angular separability of data clusters or network communities in geometrical space and its relevance to hyperbolic embedding
Alessandro Muscoloni, Carlo Vittorio Cannistraci
Analysis of 'big data' characterized by high-dimensionality such as word vectors and complex networks requires often their representation in a geometrical space by embedding. Recen…
Navigability evaluation of complex networks by greedy routing efficiency
Alessandro Muscoloni, Carlo Vittorio Cannistraci
Network navigability is a key feature of complex networked systems. For a network embedded in a geometrical space, maximization of greedy routing (GR) measures based on the node ge…