Cikkek nyilvánosan hozzáférhető megbízással - Laks V.S. LakshmananTovábbi információ
Sehol sem hozzáférhető: 2
To intervene or not to intervene: Cost based intervention for combating fake news
S Thirumuruganathan, M Simpson, LVS Lakshmanan
Proceedings of the 2021 International Conference on Management of Data, 2300 …, 2021
Megbízások: Natural Sciences and Engineering Research Council of Canada
TSA: A truthful mechanism for social advertising
T Grubenmann, RCK Cheng, LVS Lakshmanan
Proceedings of the 13th International Conference on Web Search and Data …, 2020
Megbízások: Natural Sciences and Engineering Research Council of Canada, Research Grants …
Valahol hozzáférhető: 17
Efficient network aware search in collaborative tagging sites
SA Yahia, M Benedikt, LVS Lakshmanan, J Stoyanovich
Proceedings of the VLDB Endowment 1 (1), 710-721, 2008
Megbízások: US National Institutes of Health
Revisiting the stop-and-stare algorithms for influence maximization
K Huang, S Wang, G Bevilacqua, X Xiao, LVS Lakshmanan
Proceedings of the VLDB Endowment 10 (9), 913-924, 2017
Megbízások: Natural Sciences and Engineering Research Council of Canada
Truss decomposition of probabilistic graphs: Semantics and algorithms
X Huang, W Lu, LVS Lakshmanan
Proceedings of the 2016 International Conference on Management of Data, 77-90, 2016
Megbízások: Natural Sciences and Engineering Research Council of Canada
Model-independent online learning for influence maximization
S Vaswani, B Kveton, Z Wen, M Ghavamzadeh, LVS Lakshmanan, ...
International conference on machine learning, 3530-3539, 2017
Megbízások: Natural Sciences and Engineering Research Council of Canada
Community search over big graphs: Models, algorithms, and opportunities
X Huang, LVS Lakshmanan, J Xu
2017 IEEE 33rd international conference on data engineering (ICDE), 1451-1454, 2017
Megbízások: Natural Sciences and Engineering Research Council of Canada, Research Grants …
Efficient algorithms for densest subgraph discovery on large directed graphs
C Ma, Y Fang, R Cheng, LVS Lakshmanan, W Zhang, X Lin
Proceedings of the 2020 ACM SIGMOD International Conference on Management of …, 2020
Megbízások: National Natural Science Foundation of China, Research Grants Council, Hong Kong
Linc: a motif counting algorithm for uncertain graphs
C Ma, R Cheng, LVS Lakshmanan, T Grubenmann, Y Fang, X Li
Proceedings of the VLDB Endowment 13 (2), 155-168, 2019
Megbízások: Natural Sciences and Engineering Research Council of Canada, Research Grants …
Efficient approximation algorithms for adaptive seed minimization
J Tang, K Huang, X Xiao, LVS Lakshmanan, X Tang, A Sun, A Lim
Proceedings of the 2019 International Conference on Management of Data, 1096 …, 2019
Megbízások: Natural Sciences and Engineering Research Council of Canada, National …
A convex-programming approach for efficient directed densest subgraph discovery
C Ma, Y Fang, R Cheng, LVS Lakshmanan, X Han
Proceedings of the 2022 International Conference on Management of Data, 845-859, 2022
Megbízások: Natural Sciences and Engineering Research Council of Canada, National …
On directed densest subgraph discovery
C Ma, Y Fang, R Cheng, LVS Lakshmanan, W Zhang, X Lin
ACM Transactions on Database Systems (TODS) 46 (4), 1-45, 2021
Megbízások: Natural Sciences and Engineering Research Council of Canada, National …
Maximizing welfare in social networks under a utility driven influence diffusion model
P Banerjee, W Chen, LVS Lakshmanan
Proceedings of the 2019 international conference on management of data, 1078 …, 2019
Megbízások: Natural Sciences and Engineering Research Council of Canada, National …
Finding locally densest subgraphs: a convex programming approach
C Ma, R Cheng, LVS Lakshmanan, X Han
Proceedings of the VLDB Endowment 15 (11), 2719-2732, 2022
Megbízások: Natural Sciences and Engineering Research Council of Canada
Efficient directed densest subgraph discovery
C Ma, Y Fang, R Cheng, LVS Lakshmanan, W Zhang, X Lin
ACM SIGMOD Record 50 (1), 33-40, 2021
Megbízások: Natural Sciences and Engineering Research Council of Canada, Research Grants …
Efficient and effective algorithms for revenue maximization in social advertising
K Han, B Wu, J Tang, S Cui, C Aslay, LVS Lakshmanan
Proceedings of the 2021 international conference on management of data, 671-684, 2021
Megbízások: Natural Sciences and Engineering Research Council of Canada
Accelerating directed densest subgraph queries with software and hardware approaches
C Ma, Y Fang, R Cheng, LVS Lakshmanan, X Han, X Li
The VLDB Journal 33 (1), 207-230, 2024
Megbízások: Natural Sciences and Engineering Research Council of Canada, National …
Voting-based opinion maximization
A Saha, X Ke, A Khan, LVS Lakshmanan
2023 IEEE 39th International Conference on Data Engineering (ICDE), 544-557, 2023
Megbízások: Natural Sciences and Engineering Research Council of Canada
MOSER: Scalable network motif discovery using serial test
MM Najafi, C Ma, X Li, R Cheng, LVS Lakshmanan
Proceedings of the VLDB Endowment 17 (3), 591-603, 2023
Megbízások: Natural Sciences and Engineering Research Council of Canada, National …
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