Calvin Lab Auditorium
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.