activity
20192021
most citedEstimating Node Importance in Knowledge Graphs Using Graph Neural Networks

126 citations · 241 across the 7 of their papers we have counts for

collaborators

9 papers

stat.ME2021

Spatially and Robustly Hybrid Mixture Regression Model for Inference of Spatial Dependence

Wennan Chang, Pengtao Dang, Changlin Wan +7

In this paper, we propose a Spatial Robust Mixture Regression model to investigate the relationship between a response variable and a set of explanatory variables over the spatial…

cs.LG20204 cited

Denoising individual bias for a fairer binary submatrix detection

Changlin Wan, Wennan Chang, Tong Zhao +2

Low rank representation of binary matrix is powerful in disentangling sparse individual-attribute associations, and has received wide applications. Existing binary matrix factoriza…

cs.LG2020

Geometric All-Way Boolean Tensor Decomposition

Changlin Wan, Wennan Chang, Tong Zhao +2

Boolean tensor has been broadly utilized in representing high dimensional logical data collected on spatial, temporal and/or other relational domains. Boolean Tensor Decomposition…

cs.AI202069 cited

AutoKnow: Self-Driving Knowledge Collection for Products of Thousands of Types

Xin Luna Dong, Xiang He, Andrey Kan +19

Can one build a knowledge graph (KG) for all products in the world? Knowledge graphs have firmly established themselves as valuable sources of information for search and question a…

cs.LG202022 cited

MultiImport: Inferring Node Importance in a Knowledge Graph from Multiple Input Signals

Namyong Park, Andrey Kan, Xin Luna Dong +2

Given multiple input signals, how can we infer node importance in a knowledge graph (KG)? Node importance estimation is a crucial and challenging task that can benefit a lot of app…

cs.CL202018 cited

Octet: Online Catalog Taxonomy Enrichment with Self-Supervision

Yuning Mao, Tong Zhao, Andrey Kan +4

Taxonomies have found wide applications in various domains, especially online for item categorization, browsing, and search. Despite the prevalent use of online catalog taxonomies,…