Abstract
Real world large graphs and networks often exhibit complex hierarchical structure, which goes beyond what can be uncovered by traditional linear algebra tools, such as eigendecomposition. In this talk I describe a new notion of matrix factorization inspired by multiresolution analysis that can capture structure at multiple scales. Multiresolution Matrix Factorizations (MMFs) both provide a model for graphs with multiscale structure, as well as a wavelet basis for approximating functions on such graphs. The work presented in this talk is joint with Nedelina Teneva and Vikas Garg.