2 citations · 3 across the 7 of their papers we have counts for
8 papers
Geometric bias in eigenspace perturbation under random heterogeneous noise
Fengkai Liu, Ke Wang, Wanjie Wang
Spectral methods rely on the stability of principal eigenspaces under random perturbations. Classically, this is quantified by the Davis-Kahan and Wedin theorems, which bound the e…
Inlier Recovery for Robust Registration via Gram-Matrix Overlap
Ruizi Wu, Yuehaw Khoo, Wanjie Wang
Robust point-set registration in the presence of noise and outliers is challenging because the matched points (inliers) must be identified before reliable alignment can be performe…
Community Detection on Inhomogeneous Multilayer Networks with Extreme Sparsity
Tao Shen, Wanjie Wang
We study layer-specific community detection in an -layer network on a common set of nodes. Because modern networks are constructed from multi-modal d…
i-IF-Learn: Iterative Feature Selection and Unsupervised Learning for High-Dimensional Complex Data
Chen Ma, Wanjie Wang, Shuhao Fan
Unsupervised learning of high-dimensional data is challenging due to irrelevant or noisy features obscuring underlying structures. It's common that only a few features, called the…
Gradient Descent Algorithm Survey
Deng Fucheng, Wang Wanjie, Gong Ao +2
Focusing on the practical configuration needs of optimization algorithms in deep learning, this article concentrates on five major algorithms: SGD, Mini-batch SGD, Momentum, Adam,…
Optimal Network-Guided Covariate Selection for High-Dimensional Data Integration
Tao Shen, Wanjie Wang
Modern data often arises with multiple modalities. For example, covariates and a network are observed on the same subjects, and both contain useful information. Effectively integra…
Spectral Clustering on Multilayer Networks with Covariates
Da Zhao, Wanjie Wang, Jialiang Li
The community detection problem on multilayer networks have drawn much interest. When the nodal covariates ar also present, few work has been done to integrate information from bot…
Permutation Recovery on Manifold Data via Spectral Seriation
Yuehaw Khoo, Xin T. Tong, Wanjie Wang +1
Data points in many scientific experiments originate from an ordered structure, yet this ordering is often unavailable.We consider noisy data points with the correct ordering to be…