
2022
1
Finding Locally Densest Subgraphs: A Convex-Programming Approach
Proc. VLDB Endow. 15(2022). Also in the Very Large Databases Conf. (VLDB 2022), Sydney, Australia, Sep 2022
C. Ma*, R. Cheng, L. Lakshmanan, and X. Han
2022
2
DeepTEA: Effective and Efficient Online Time-dependent Trajectory Outlier Detection
Proc. VLDB Endow. 15(2022). Also in the Very Large Databases Conf. (VLDB 2022), Sydney, Australia, Sep 2022
2022
3
A Convex-Programming Approach for Efficient Directed Densest Subgraph Discovery
ACM SIGMOD Conference 2022, June 2022, Philadelphia, PA, USA
C. Ma*, Y. Fang, R. Cheng, L. Lakshmanan, and X. Han
2021
6
On Analyzing Graphs with Motif-Paths
Proc. VLDB Endow. 14(6): 1111-1123 (2021). Also in the Very Large Databases Conf. (VLDB 2021), Copenhagen, Aug 2021.
2021
7
Fast Augmentation Algorithms for Network Kernel Density Visualization
Proc. VLDB Endow.14(9): 1503-1516 (2021). Also in the Very Large Databases Conf. (VLDB 2021), Copenhagen, Aug 2021.
T. N. Chan*, Z. Li, L. H. U, J. Xu, and R. Cheng.
2019
12
A Crowdsourcing Framework for Collecting Tabular Data
C. Shan*, N. Mamoulis, G. Li, R. Cheng, Z. Huang*, and Y. Zheng*.
2017
33
TOAIN: A Throughput Optimizing Adaptive Index for Answering Dynamic kNN Queries on Road Networks
In Proceedings of the VLDB Endowment (PVLDB), 11(5), pp. 594-606, Jan 2018. Also in the Very Large Databases Conf. (VLDB 2018), Rio De Janeiro, Brazil, Aug 27-31, 2018.
S. Luo*, B. Kao, G. Li, J. Hu*, R. Cheng, and Y. Zheng*.
2015
39
Discovering Meta-Paths in Large Heterogeneous Information Networks
In the 24th Intl. World Wide Web Conf. (WWW 2015), Florence, Italy, May 2015.[ Talk ]
Changping Meng, Reynold Cheng, Silviu Maniu, Pierre Senellart, and Wangda Zhang.
Note: A “*” before the author name means he/she is my postdoc. fellow, graduate student, or research assistant.