Rundong Li

Orcid: 0000-0003-0354-9536

Affiliations:
  • Xi'an Jiaotong University, China


According to our database1, Rundong Li authored at least 12 papers between 2021 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Privacy-Preserving Sketches for Securely Estimating Intersection Cardinality Over Distributed Data Sets.
IEEE Trans. Dependable Secur. Comput., 2026

ZRing: A Dynamic Sketch for Weighted Cardinality Estimation in Data Streams.
Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1, 2026

2025
Efficient and Accurate Differentially Private Cardinality Continual Releases.
Proc. ACM Manag. Data, June, 2025

Poisoning Attacks and Defenses to Learned Bloom Filters for Malicious URL Detection.
IEEE Trans. Dependable Secur. Comput., 2025

2024
Sketching Data Distribution by Rotation.
IEEE Trans. Knowl. Data Eng., November, 2024

Half-Xor: A Fully-Dynamic Sketch for Estimating the Number of Distinct Values in Big Tables.
IEEE Trans. Knowl. Data Eng., July, 2024

An LDP Compatible Sketch for Securely Approximating Set Intersection Cardinalities.
Proc. ACM Manag. Data, February, 2024

QSketch: An Efficient Sketch for Weighted Cardinality Estimation in Streams.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

A Compact and Accurate Sketch for Estimating a Large Range of Set Difference Cardinalities.
Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

2022
Approximately Counting Butterflies in Large Bipartite Graph Streams.
IEEE Trans. Knowl. Data Eng., 2022

2021
Building Fast and Compact Sketches for Approximately Multi-Set Multi-Membership Querying.
Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

Fast Rotation Kernel Density Estimation over Data Streams.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021


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