7 citations · 13 across the 8 of their papers we have counts for
8 papers
Projected Tensor Power Method for Hypergraph Community Recovery
Jinxin Wang, Yuen-Man Pun, Xiaolu Wang +2
This paper investigates the problem of exact community recovery in the symmetric -uniform hypergraph stochastic block model (-HSBM). In this model, a -uniform…
A Linearly Convergent Algorithm for Rotationally Invariant -Norm Principal Component Analysis
Taoli Zheng, Peng Wang, Anthony Man-Cho So
To do dimensionality reduction on the datasets with outliers, the -norm principal component analysis (L1-PCA) as a typical robust alternative of the conventional PCA has en…
Convergence and Recovery Guarantees of the K-Subspaces Method for Subspace Clustering
Peng Wang, Huikang Liu, Anthony Man-Cho So +1
The K-subspaces (KSS) method is a generalization of the K-means method for subspace clustering. In this work, we present local convergence analysis and a recovery guarantee for KSS…
Repro Samples Method for Finite- and Large-Sample Inferences
Min-ge Xie, Peng Wang
This article presents a novel, general, and effective simulation-inspired approach, called {\it repro samples method}, to conduct statistical inference. The approach studies the pe…
Exact Community Recovery over Signed Graphs
Xiaolu Wang, Peng Wang, Anthony Man-Cho So
Signed graphs encode similarity and dissimilarity relationships among different entities with positive and negative edges. In this paper, we study the problem of community recovery…
Linear Convergence of a Proximal Alternating Minimization Method with Extrapolation for -Norm Principal Component Analysis
Peng Wang, Huikang Liu, Anthony Man-Cho So
A popular robust alternative of the classic principal component analysis (PCA) is the -norm PCA (L1-PCA), which aims to find a subspace that captures the most variation in…
Optimal Non-Convex Exact Recovery in Stochastic Block Model via Projected Power Method
Peng Wang, Huikang Liu, Zirui Zhou +1
In this paper, we study the problem of exact community recovery in the symmetric stochastic block model, where a graph of vertices is randomly generated by partitioning the ver…
Non-Convex Exact Community Recovery in Stochastic Block Model
Peng Wang, Zirui Zhou, Anthony Man-Cho So
Community detection in graphs that are generated according to stochastic block models (SBMs) has received much attention lately. In this paper, we focus on the binary symmetric SBM…