4 papers
Adversarial Deep Network Embedding for Cross-network Node Classification
Xiao Shen, Quanyu Dai, Fu-lai Chung +2
In this paper, the task of cross-network node classification, which leverages the abundant labeled nodes from a source network to help classify unlabeled nodes in a target network,…
Coalescence estimates for the corner growth model with exponential weights
Timo Seppäläinen, Xiao Shen
We establish estimates for the coalescence time of semi-infinite directed geodesics in the planar corner growth model with i.i.d. exponential weights. There are four estimates: upp…
Adversarial Training Methods for Network Embedding
Quanyu Dai, Xiao Shen, Liang Zhang +2
Network Embedding is the task of learning continuous node representations for networks, which has been shown effective in a variety of tasks such as link prediction and node classi…
Deep Network Embedding for Graph Representation Learning in Signed Networks
Xiao Shen, Fu-Lai Chung
Network embedding has attracted an increasing attention over the past few years. As an effective approach to solve graph mining problems, network embedding aims to learn a low-dime…