Statistical Analysis of Massive Data Streams: Proceedings of a Workshop (2004)
Chapter: Kevin Vixie Incorporating Invariants in Mahalanobis Distance-Based Classifiers: Applications to Face Recognition
Kevin Vixie
Incorporating Invariants in Mahalanobis Distance-Based Classifiers: Applications to Face Recognition
Transcript of Presentation
Technical Paper
BIOSKETCH: Kevin Vixie is a mathematician in the computational science methods group at Los Alamos National Laboratory. His research interests are in inverse problems; image analysis and data-driven approximation; computation; and modeling. More specifically, he is interested in the following main areas: data analysis techniques inspired by ideas from partial differential equations, functional analysis, and dynamical systems; nonlinear functional analysis and its applications to real world problems; geometric measure theory and image analysis; high dimensional approximation and data analysis; and inverse problems, especially sparse tomography. The problems he is interested in tend to have a strong geometrical flavor and a focus not too far from the mathematical/real data interface.
