PhD Seminar • Algorithms and Complexity — Geodesic Convexity in Statistics and Sample Complexity Bounds
Please note: This PhD seminar will be given online.
Akshay Ramachandran, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Lap Chi Lau
The matrix normal model, the family of Gaussian matrix-variate distributions whose covariance matrix is the Kronecker product of two lower dimensional factors, is frequently used to model matrix-variate data. The tensor normal model generalizes this family to Kronecker products of three or more factors.