1.8k citations · 2.3k across the 59 of their papers we have counts for
8 papers · 1 filter
Incremental Eigenpair Computation for Graph Laplacian Matrices: Theory and Applications
Pin-Yu Chen, Baichuan Zhang, Mohammad Al Hasan
The smallest eigenvalues and the associated eigenvectors (i.e., eigenpairs) of a graph Laplacian matrix have been widely used in spectral clustering and community detection. Howeve…
Revisiting Spectral Graph Clustering with Generative Community Models
Pin-Yu Chen, Lingfei Wu
The methodology of community detection can be divided into two principles: imposing a network model on a given graph, or optimizing a designed objective function. The former provid…
Principled Multilayer Network Embedding
Weiyi Liu, Pin-Yu Chen, Sailung Yeung +2
Multilayer network analysis has become a vital tool for understanding different relationships and their interactions in a complex system, where each layer in a multilayer network d…
Multilayer Spectral Graph Clustering via Convex Layer Aggregation: Theory and Algorithms
Pin-Yu Chen, Alfred O. Hero
Multilayer graphs are commonly used for representing different relations between entities and handling heterogeneous data processing tasks. Non-standard multilayer graph clustering…
ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Networks without Training Substitute Models
Pin-Yu Chen, Huan Zhang, Yash Sharma +2
Deep neural networks (DNNs) are one of the most prominent technologies of our time, as they achieve state-of-the-art performance in many machine learning tasks, including but not l…
Can GAN Learn Topological Features of a Graph?
Weiyi Liu, Pin-Yu Chen, Hal Cooper +3
This paper is first-line research expanding GANs into graph topology analysis. By leveraging the hierarchical connectivity structure of a graph, we have demonstrated that generativ…