155 citations · 888 across the 24 of their papers we have counts for
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Exact Camera Location Recovery by Least Unsquared Deviations
Gilad Lerman, Yunpeng Shi, Teng Zhang
We establish exact recovery for the Least Unsquared Deviations (LUD) algorithm of Ozyesil and Singer. More precisely, we show that for sufficiently many cameras with given corrupte…
Anisotropic twicing for single particle reconstruction using autocorrelation analysis
Tejal Bhamre, Teng Zhang, Amit Singer
The missing phase problem in X-ray crystallography is commonly solved using the technique of molecular replacement, which borrows phases from a previously solved homologous structu…
Denoising and Covariance Estimation of Single Particle Cryo-EM Images
Tejal Bhamre, Teng Zhang, Amit Singer
The problem of image restoration in cryo-EM entails correcting for the effects of the Contrast Transfer Function (CTF) and noise. Popular methods for image restoration include `pha…
Orthogonal Matrix Retrieval in Cryo-Electron Microscopy
Tejal Bhamre, Teng Zhang, Amit Singer
In single particle reconstruction (SPR) from cryo-electron microscopy (cryo-EM), the 3D structure of a molecule needs to be determined from its 2D projection images taken at unknow…
Hybrid Linear Modeling via Local Best-fit Flats
Teng Zhang, Arthur Szlam, Yi Wang +1
We present a simple and fast geometric method for modeling data by a union of affine subspaces. The method begins by forming a collection of local best-fit affine subspaces, i.e.,…
Randomized hybrid linear modeling by local best-fit flats
Teng Zhang, Arthur Szlam, Yi Wang +1
The hybrid linear modeling problem is to identify a set of d-dimensional affine sets in a D-dimensional Euclidean space. It arises, for example, in object tracking and structure fr…
Median K-flats for hybrid linear modeling with many outliers
Teng Zhang, Arthur Szlam, Gilad Lerman
We describe the Median K-Flats (MKF) algorithm, a simple online method for hybrid linear modeling, i.e., for approximating data by a mixture of flats. This algorithm simultaneously…