N. Huang

Subzero matrix completion for sparse data analysis: large-scale learning of latent low-rank structure

A stochastic, alternating least-squares algorithm that operates on smaller blocks of this dense matrix and scales as a result to much larger problems and is used to analyze the sparse matrix of synaptic weights for the recently published $\textit{Drosphilia}$ connectome.