479 citations · 1.9k across the 94 of their papers we have counts for
9 papers · 1 filter
Linear and Range Counting under Metric-based Local Differential Privacy
Zhuolun Xiang, Bolin Ding, Xi He +1
Local differential privacy (LDP) enables private data sharing and analytics without the need for a trusted data collector. Error-optimal primitives (for, e.g., estimating means and…
Bayes EMbedding (BEM): Refining Representation by Integrating Knowledge Graphs and Behavior-specific Networks
Yuting Ye, Xuwu Wang, Jiangchao Yao +4
Low-dimensional embeddings of knowledge graphs and behavior graphs have proved remarkably powerful in varieties of tasks, from predicting unobserved edges between entities to conte…
Improving Utility and Security of the Shuffler-based Differential Privacy
Tianhao Wang, Bolin Ding, Min Xu +5
When collecting information, local differential privacy (LDP) alleviates privacy concerns of users because their private information is randomized before being sent it to the centr…
A Survey and Experimental Analysis of Distributed Subgraph Matching
Longbin Lai, Zhu Qing, Zhengyi Yang +10
Recently there emerge many distributed algorithms that aim at solving subgraph matching at scale. Existing algorithm-level comparisons failed to provide a systematic view to the pr…
Sequential Scenario-Specific Meta Learner for Online Recommendation
Zhengxiao Du, Xiaowei Wang, Hongxia Yang +2
Cold-start problems are long-standing challenges for practical recommendations. Most existing recommendation algorithms rely on extensive observed data and are brittle to recommend…
Is a Single Vector Enough? Exploring Node Polysemy for Network Embedding
Ninghao Liu, Qiaoyu Tan, Yuening Li +3
Networks have been widely used as the data structure for abstracting real-world systems as well as organizing the relations among entities. Network embedding models are powerful to…
Representation Learning for Attributed Multiplex Heterogeneous Network
Yukuo Cen, Xu Zou, Jianwei Zhang +3
Network embedding (or graph embedding) has been widely used in many real-world applications. However, existing methods mainly focus on networks with single-typed nodes/edges and ca…
Towards Knowledge-Based Personalized Product Description Generation in E-commerce
Qibin Chen, Junyang Lin, Yichang Zhang +3
Quality product descriptions are critical for providing competitive customer experience in an e-commerce platform. An accurate and attractive description not only helps customers m…
AliGraph: A Comprehensive Graph Neural Network Platform
Rong Zhu, Kun Zhao, Hongxia Yang +5
An increasing number of machine learning tasks require dealing with large graph datasets, which capture rich and complex relationship among potentially billions of elements. Graph…