2020
Matrix Completion with Hierarchical Graph Side Information
NeurIPS 2020poster
We consider a matrix completion problem that exploits social or item similarity graphs as side information. We develop a universal, parameter-free, and computationally efficient algorithm that starts with hierarchical graph clustering and then iteratively refines estimates both on graph clustering a…