T
Teng Zhang
Researcher at University of Central Florida
Publications - 80
Citations - 2321
Teng Zhang is an academic researcher from University of Central Florida. The author has contributed to research in topics: Linear subspace & Convex optimization. The author has an hindex of 23, co-authored 75 publications receiving 1971 citations. Previous affiliations of Teng Zhang include Princeton University & University of Minnesota.
Papers
More filters
Journal ArticleDOI
Hybrid Linear Modeling via Local Best-Fit Flats
TL;DR: This work presents a simple and fast geometric method for modeling data by a union of affine subspaces, and gives extensive experimental evidence demonstrating the state of the art accuracy and speed of the suggested algorithms on these problems.
Proceedings ArticleDOI
Median K-flats for hybrid linear modeling with many outliers
TL;DR: The MedianK-flats (MKF) algorithm is described, a simple online method for hybrid linear modeling, i.e., for approximating data by a mixture of flats, which simultaneously partitions the data into clusters while finding their corresponding best approximating ℓ1 d-Flats.
Journal Article
A novel M-estimator for robust PCA
Teng Zhang,Gilad Lerman +1 more
TL;DR: The minimizer and its subspace are interpreted as robust versions of the empirical inverse covariance and the PCA subspace respectively and compared with many other algorithms for robust PCA on synthetic and real data sets and demonstrate state-of-the-art speed and accuracy.
Journal ArticleDOI
Sparse precision matrix estimation via lasso penalized D-trace loss
Teng Zhang,Hui Zou +1 more
TL;DR: A novel sparse precision matrix estimator is defined as the minimizer of the lasso penalized D-trace loss under a positive-definiteness constraint and is shown to have the sparse recovery property.
Journal ArticleDOI
Robust Computation of Linear Models by Convex Relaxation
TL;DR: In this article, a convex optimization problem, called reaper, is described that can reliably fit a low-dimensional model to this type of data, and an efficient algorithm for solving the reaper problem is provided.