Substantial progress has been made recently on develo** provably accurate and efficient
algorithms for low-rank matrix factorization via nonconvex optimization. While conventional …

In recent years, an abundance of new molecular structures have been elucidated using cryo-
electron microscopy (cryo-EM), largely due to advances in hardware technology and data …

Simultaneous localization and map** (SLAM) consists in the concurrent construction of a
model of the environment (the map), and the estimation of the state of the robot moving …

The structure from motion (SfM) problem in computer vision is to recover the three-
dimensional (3D) structure of a stationary scene from a set of projective measurements …

Spectral methods have emerged as a simple yet surprisingly effective approach for
extracting information from massive, noisy and incomplete data. In a nutshell, spectral …

In this paper, we study the problem of semantic annotation on 3D models that are
represented as shape graphs. A functional view is taken to represent localized information …

We consider a family of algorithms that successively sample and minimize simple stochastic
models of the objective function. We show that under reasonable conditions on …

Recovering low-rank structures via eigenvector perturbation analysis is a common problem
in statistical machine learning, such as in factor analysis, community detection, ranking …

Many important geometric estimation problems naturally take the form of synchronization
over the special Euclidean group: estimate the values of a set of unknown group elements x …

Euclidean distance geometry is the study of Euclidean geometry based on the concept of
distance. This is useful in several applications where the input data consist of an incomplete …