IEEE Transactions on Pattern Analysis and Machine…

14 October 2010

In this paper, we address the subspace clustering problem. Given a set of data samples (vectors) approximately drawn from a union of multiple subspaces, our goal is to cluster the samples into their… Expand

We prove that when the measurement vectors $$\varvec{a}_k$$ak’s are generic (i.e., length-n complex vector) and numerous enough, a natural least-squares formulation for GPR has the following benign geometric structure.Expand

We give the first efficient algorithm that provably recovers a complete (i.e., square and invertible) matrix from a nonconvex optimization problem with a spherical constraint that is highly structured with high probability.Expand

The problem of recognizing actions in realistic videos is challenging yet absorbing owing to its great potentials in many practical applications.Expand

We focus on smooth nonconvex optimization problems that obey: (1) all local minimizers are also global; and (2) the objective has a negative directional curvature.Expand

We consider the problem of recovering a complete (i.e., square and invertible) matrix <inline-formula> <tex-math notation="LaTeX">$ A_{0}$ from arbitrary initializations using a Riemannian trust region algorithm.Expand

Low-Rank Representation with Positive Semi Definite constraint, or LRR-PSD, can be solved in an exquisite scheme efficiently instead of general-purpose SDP solvers that usually scale up poorly.Expand