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20092026
most citedFeature Inference Attack on Model Predictions in Vertical Federated Learning

210 citations · 1.2k across the 48 of their papers we have counts for

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18 papers · 1 filter

cs.DB2023★ 5 cited

PrivLava: Synthesizing Relational Data with Foreign Keys under Differential Privacy

Kuntai Cai, Xiaokui Xiao, Graham Cormode

Answering database queries while preserving privacy is an important problem that has attracted considerable research attention in recent years. A canonical approach to this problem…

cs.DB2020

Analysis of Indexing Structures for Immutable Data

Cong Yue, Zhongle Xie, Meihui Zhang +4

In emerging applications such as blockchains and collaborative data analytics, there are strong demands for data immutability, multi-version accesses, and tamper-evident controls.…

cs.DB2020★ 1 cited

Realtime Index-Free Single Source SimRank Processing on Web-Scale Graphs

Jieming Shi, Tianyuan Jin, Renchi Yang +2

Given a graph G and a node u in G, a single source SimRank query evaluates the similarity between u and every node v in G. Existing approaches to single source SimRank computation…

cs.DB2017★ 37 cited

ProbeSim: Scalable Single-Source and Top-k SimRank Computations on Dynamic Graphs

Yu Liu, Bolong Zheng, Xiaodong He +4

Single-source and top- SimRank queries are two important types of similarity search in graphs with numerous applications in web mining, social network analysis, spam detection,…

cs.DB2016★ 162 cited

Collecting and Analyzing Data from Smart Device Users with Local Differential Privacy

Thông T. Nguyên, Xiaokui Xiao, Yin Yang +3

Organizations with a large user base, such as Samsung and Google, can potentially benefit from collecting and mining users' data. However, doing so raises privacy concerns, and ris…

cs.DB2016★ 8 cited

SLING: A Near-Optimal Index Structure for SimRank

Boyu Tian, Xiaokui Xiao

SimRank is a similarity measure for graph nodes that has numerous applications in practice. Scalable SimRank computation has been the subject of extensive research for more than a…