9 citations · 15 across the 4 of their papers we have counts for
4 papers · 1 filter
Fast algorithms for robust principal component analysis with an upper bound on the rank
Ningyu Sha, Lei Shi, Ming Yan
The robust principal component analysis (RPCA) decomposes a data matrix into a low-rank part and a sparse part. There are mainly two types of algorithms for RPCA. The first type of…
A Novel Regularization Based on the Error Function for Sparse Recovery
Weihong Guo, Yifei Lou, Jing Qin +1
Regularization plays an important role in solving ill-posed problems by adding extra information about the desired solution, such as sparsity. Many regularization terms usually inv…
Variational Asymptotic Preserving Scheme for the Vlasov-Poisson-Fokker-Planck System
Jose A. Carrillo, Li Wang, Wuzhe Xu +1
We design a variational asymptotic preserving scheme for the Vlasov-Poisson-Fokker-Planck system with the high field scaling, which describes the Brownian motion of a large system…
Accelerated Schemes for the Minimization
Chao Wang, Ming Yan, Yaghoub Rahimi +1
In this paper, we consider the minimization for sparse recovery and study its relationship with the - model. Based on this relationship, we propose three nu…