68 citations · 78 across the 8 of their papers we have counts for
8 papers
Two-way Node Popularity Model for Directed and Bipartite Networks
Bing-Yi Jing, Ting Li, Jiangzhou Wang +1
There has been extensive research on community detection in directed and bipartite networks. However, these studies often fail to consider the popularity of nodes in different comm…
Optimal Clustering of Discrete Mixtures: Binomial, Poisson, Block Models, and Multi-layer Networks
Zhongyuan Lyu, Ting Li, Dong Xia
In this paper, we first study the fundamental limit of clustering networks when a multi-layer network is present. Under the mixture multi-layer stochastic block model (MMSBM), we s…
rMultiNet: An R Package For Multilayer Networks Analysis
Ting Li, Zhongyuan Lyu, Chenyu Ren +1
This paper develops an R package rMultiNet to analyze multilayer network data. We provide two general frameworks from recent literature, e.g. mixture multilayer stochastic block mo…
Regularized Graph Structure Learning with Semantic Knowledge for Multi-variates Time-Series Forecasting
Hongyuan Yu, Ting Li, Weichen Yu +4
Multivariate time-series forecasting is a critical task for many applications, and graph time-series network is widely studied due to its capability to capture the spatial-temporal…
Community Detection on Mixture Multi-layer Networks via Regularized Tensor Decomposition
Bing-Yi Jing, Ting Li, Zhongyuan Lyu +1
We study the problem of community detection in multi-layer networks, where pairs of nodes can be related in multiple modalities. We introduce a general framework, i.e., mixture mul…
Measuring the Clustering Strength of a Network via the Normalized Clustering Coefficient
Ting Li, Xianshi Yu, Bing-Yi Jing
In this paper, we propose a novel statistic of networks, the normalized clustering coefficient, which is a modified version of the clustering coefficient that is robust to network…
Semi-supervised learning in unbalanced and heterogeneous networks
Ting Li, Ningchen Ying, Xianshi Yu +1
Community detection was a hot topic on network analysis, where the main aim is to perform unsupervised learning or clustering in networks. Recently, semi-supervised learning has re…
Adaptive Scaling
Ting Li, Bingyi Jing, Ningchen Ying +1
Preprocessing data is an important step before any data analysis. In this paper, we focus on one particular aspect, namely scaling or normalization. We analyze various scaling meth…