Estimation of Subspace Arrangements: Its Algebra and Statistics

Algebraically, we study the properties of polynomials vanishing on a union of subspaces; and statistically, we study how to estimate these polynomials robustly from real sample sets with noise and outliers. These new methods in many ways improve and generalize extant methods for modeling or clustering mixed data. Finally, we will show results of these methods applied to computer vision and image processing.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Electrical and Computer Engineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2015

Author dc:creator

• Yang, Allen

Contributors dc:contributor

• Ma, Yi

• Engineering, Electronics and Electrical

Language dc:language

eng

Identifier

(MiAaPQ)AAI3243032

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/80988