26 citations · 53 across the 4 of their papers we have counts for
4 papers
ATP: Directed Graph Embedding with Asymmetric Transitivity Preservation
Jiankai Sun, Bortik Bandyopadhyay, Armin Bashizade +3
Directed graphs have been widely used in Community Question Answering services (CQAs) to model asymmetric relationships among different types of nodes in CQA graphs, e.g., question…
MILE: A Multi-Level Framework for Scalable Graph Embedding
Jiongqian Liang, Saket Gurukar, Srinivasan Parthasarathy
Recently there has been a surge of interest in designing graph embedding methods. Few, if any, can scale to a large-sized graph with millions of nodes due to both computational com…
Semi-supervised Embedding in Attributed Networks with Outliers
Jiongqian Liang, Peter Jacobs, Jiankai Sun +1
In this paper, we propose a novel framework, called Semi-supervised Embedding in Attributed Networks with Outliers (SEANO), to learn a low-dimensional vector representation that sy…
Robust Contextual Outlier Detection: Where Context Meets Sparsity
Jiongqian Liang, Srinivasan Parthasarathy
Outlier detection is a fundamental data science task with applications ranging from data cleaning to network security. Given the fundamental nature of the task, this has been the s…