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ORCIDLaks V. S. Lakshmanan
V. S. Lakshmanan 0001
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- affiliation: University of British Columbia, Department of Computer Science
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2020 – today
- 2024
[j76]Rudra Ranajee Saha, Laks V. S. Lakshmanan, Raymond T. Ng:
Stance Detection with Explanations. Comput. Linguistics 50(1): 193-235 (2024)- [j75]Chenhao Ma
, Yixiang Fang, Reynold Cheng, Laks V. S. Lakshmanan, Xiaolin Han, Xiaodong Li:
Accelerating directed densest subgraph queries with software and hardware approaches. VLDB J. 33(1): 207-230 (2024) - [c182]Ganesh Jawahar, Haichuan Yang, Yunyang Xiong, Zechun Liu, Dilin Wang, Fei Sun, Meng Li, Aasish Pappu, Barlas Oguz, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan, Raghuraman Krishnamoorthi, Vikas Chandra:
Mixture-of-Supernets: Improving Weight-Sharing Supernet Training with Architecture-Routed Mixture-of-Experts. ACL (Findings) 2024: 10424-10443 - [c181]Ganesh Jawahar, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan, Dujian Ding:
LLM Performance Predictors are good initializers for Architecture Search. ACL (Findings) 2024: 10540-10560 - [c180]Dujian Ding, Ankur Mallick, Chi Wang, Robert Sim, Subhabrata Mukherjee, Victor Rühle, Laks V. S. Lakshmanan, Ahmed Hassan Awadallah:
Hybrid LLM: Cost-Efficient and Quality-Aware Query Routing. ICLR 2024 - [c179]Bin Xiang, Bogdan Cautis, Xiaokui Xiao, Olga Mula, Dusit Niyato, Laks V. S. Lakshmanan:
Predicting Cascading Failures with a Hyperparametric Diffusion Model. KDD 2024: 3495-3506 - [c178]Yuxi Feng, Laks V. S. Lakshmanan:
DuRE: Dual Contrastive Self Training for Semi-Supervised Relation Extraction. NAACL-HLT 2024: 540-555 - [i54]Md Tawkat Islam Khondaker, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan:
GreenLLaMA: A Framework for Detoxification with Explanations. CoRR abs/2402.15951 (2024) - [i53]Dujian Ding, Ankur Mallick, Chi Wang, Robert Sim, Subhabrata Mukherjee, Victor Rühle, Laks V. S. Lakshmanan, Ahmed Hassan Awadallah:
Hybrid LLM: Cost-Efficient and Quality-Aware Query Routing. CoRR abs/2404.14618 (2024) - [i52]Dujian Ding, Bicheng Xu, Laks V. S. Lakshmanan:
OCCAM: Towards Cost-Efficient and Accuracy-Aware Image Classification Inference. CoRR abs/2406.04508 (2024) - [i51]Yingli Zhou, Qingshuo Guo, Yi Yang, Yixiang Fang, Chenhao Ma, Laks V. S. Lakshmanan:
In-depth Analysis of Densest Subgraph Discovery in a Unified Framework. CoRR abs/2406.04738 (2024) - [i50]Bin Xiang, Bogdan Cautis, Xiaokui Xiao, Olga Mula, Dusit Niyato, Laks V. S. Lakshmanan:
Predicting Cascading Failures with a Hyperparametric Diffusion Model. CoRR abs/2406.08522 (2024) - [i49]Ningyi Liao, Haoyu Liu, Zulun Zhu, Siqiang Luo, Laks V. S. Lakshmanan:
Benchmarking Spectral Graph Neural Networks: A Comprehensive Study on Effectiveness and Efficiency. CoRR abs/2406.09675 (2024) - 2023
- [j74]Prithu Banerjee, Wei Chen, Laks V. S. Lakshmanan:
Mitigating Filter Bubbles Under a Competitive Diffusion Model. Proc. ACM Manag. Data 1(2): 175:1-175:26 (2023) - [j73]Mohammad Matin Najafi, Chenhao Ma, Xiaodong Li, Reynold Cheng, Laks V. S. Lakshmanan:
MOSER: Scalable Network Motif Discovery using Serial Test. Proc. VLDB Endow. 17(3): 591-603 (2023) - [c177]Yuxi Feng, Xiaoyuan Yi, Xiting Wang, Laks V. S. Lakshmanan, Xing Xie:
DuNST: Dual Noisy Self Training for Semi-Supervised Controllable Text Generation. ACL (1) 2023: 8760-8785 - [c176]Ganesh Jawahar, Subhabrata Mukherjee, Xiaodong Liu, Young Jin Kim, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan, Ahmed Hassan Awadallah, Sébastien Bubeck, Jianfeng Gao:
AutoMoE: Heterogeneous Mixture-of-Experts with Adaptive Computation for Efficient Neural Machine Translation. ACL (Findings) 2023: 9116-9132 - [c175]Arkaprava Saha, Xiangyu Ke, Arijit Khan, Laks V. S. Lakshmanan:
Voting-based Opinion Maximization. ICDE 2023: 544-557 - [c174]Yuxi Feng, Xiaoyuan Yi, Laks V. S. Lakshmanan, Xing Xie:
KEST: Kernel Distance Based Efficient Self-Training for Improving Controllable Text Generation. IJCAI 2023: 5049-5057 - [c173]Md Tawkat Islam Khondaker, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan:
PACT: Pretraining with Adversarial Contrastive Learning for Text Classification. IJCNLP (1) 2023: 1102-1117 - [c172]Ganesh Jawahar, Subhabrata Mukherjee, Debadeepta Dey, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan, Caio C. T. Mendes, Gustavo Henrique de Rosa, Shital Shah:
Small Character Models Match Large Word Models for Autocomplete Under Memory Constraints. SustaiNLP 2023: 274-289 - [i48]Ganesh Jawahar, Haichuan Yang, Yunyang Xiong, Zechun Liu, Dilin Wang, Fei Sun, Meng Li, Aasish Pappu, Barlas Oguz, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan, Raghuraman Krishnamoorthi, Vikas Chandra:
Mixture-of-Supernets: Improving Weight-Sharing Supernet Training with Architecture-Routed Mixture-of-Experts. CoRR abs/2306.04845 (2023) - [i47]Wensheng Luo, Chenhao Ma, Yixiang Fang, Laks V. S. Lakshmanan:
A Survey of Densest Subgraph Discovery on Large Graphs. CoRR abs/2306.07927 (2023) - [i46]Yuxi Feng, Xiaoyuan Yi, Laks V. S. Lakshmanan, Xing Xie:
KEST: Kernel Distance Based Efficient Self-Training for Improving Controllable Text Generation. CoRR abs/2306.10414 (2023) - [i45]Ganesh Jawahar, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan, Dujian Ding:
LLM Performance Predictors are good initializers for Architecture Search. CoRR abs/2310.16712 (2023) - 2022
- [j72]Michael Simpson, Laks V. S. Lakshmanan, Farnoosh Hashemi:
Misinformation Mitigation under Differential Propagation Rates and Temporal Penalties. Proc. VLDB Endow. 15(10): 2216-2229 (2022) - [j71]Chenhao Ma, Reynold Cheng, Laks V. S. Lakshmanan, Xiaolin Han:
Finding Locally Densest Subgraphs: A Convex Programming Approach. Proc. VLDB Endow. 15(11): 2719-2732 (2022) - [j70]Ali Behrouz, Farnoosh Hashemi, Laks V. S. Lakshmanan:
FirmTruss Community Search in Multilayer Networks. Proc. VLDB Endow. 16(3): 505-518 (2022) - [j69]Dujian Ding, Sihem Amer-Yahia, Laks V. S. Lakshmanan:
On Efficient Approximate Queries over Machine Learning Models. Proc. VLDB Endow. 16(4): 918-931 (2022) - [j68]Laks V. S. Lakshmanan:
Mid-Career Researcher, huh?: What just Changed? SIGMOD Rec. 51(4): 45-48 (2022) - [j67]Glenn S. Bevilacqua, Laks V. S. Lakshmanan:
A fractional memory-efficient approach for online continuous-time influence maximization. VLDB J. 31(2): 403-429 (2022) - [c171]Ganesh Jawahar, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan:
Automatic Detection of Entity-Manipulated Text using Factual Knowledge. ACL (2) 2022: 86-93 - [c170]Laks V. S. Lakshmanan:
On a Quest for Combating Filter Bubbles and Misinformation. SIGMOD Conference 2022: 2 - [c169]Chenhao Ma, Yixiang Fang, Reynold Cheng, Laks V. S. Lakshmanan, Xiaolin Han:
A Convex-Programming Approach for Efficient Directed Densest Subgraph Discovery. SIGMOD Conference 2022: 845-859 - [c168]Md Tawkat Islam Khondaker, El Moatez Billah Nagoudi, AbdelRahim A. Elmadany, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan:
A Benchmark Study of Contrastive Learning for Arabic Social Meaning. WANLP@EMNLP 2022: 63-75 - [c167]Farnoosh Hashemi, Ali Behrouz, Laks V. S. Lakshmanan:
FirmCore Decomposition of Multilayer Networks. WWW 2022: 1589-1600 - [i44]Ganesh Jawahar, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan:
Automatic Detection of Entity-Manipulated Text using Factual Knowledge. CoRR abs/2203.10343 (2022) - [i43]Ali Behrouz, Farnoosh Hashemi, Laks V. S. Lakshmanan:
FirmTruss Community Search in Multilayer Networks. CoRR abs/2205.00742 (2022) - [i42]Dujian Ding, Sihem Amer-Yahia, Laks V. S. Lakshmanan:
On Efficient Approximate Queries over Machine Learning Models. CoRR abs/2206.02845 (2022) - [i41]Michael Simpson, Farnoosh Hashemi, Laks V. S. Lakshmanan:
Misinformation Mitigation under Differential Propagation Rates and Temporal Penalties. CoRR abs/2206.11419 (2022) - [i40]Farnoosh Hashemi, Ali Behrouz, Laks V. S. Lakshmanan:
FirmCore Decomposition of Multilayer Networks. CoRR abs/2208.11200 (2022) - [i39]Arkaprava Saha, Xiangyu Ke, Arijit Khan, Laks V. S. Lakshmanan:
Voting-based Opinion Maximization. CoRR abs/2209.06756 (2022) - [i38]Ganesh Jawahar, Subhabrata Mukherjee, Debadeepta Dey, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan, Caio César Teodoro Mendes, Gustavo Henrique de Rosa, Shital Shah:
Small Character Models Match Large Word Models for Autocomplete Under Memory Constraints. CoRR abs/2210.03251 (2022) - [i37]Ganesh Jawahar, Subhabrata Mukherjee, Xiaodong Liu, Young Jin Kim, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan, Ahmed Hassan Awadallah, Sébastien Bubeck, Jianfeng Gao:
AutoMoE: Neural Architecture Search for Efficient Sparsely Activated Transformers. CoRR abs/2210.07535 (2022) - [i36]Md Tawkat Islam Khondaker, El Moatez Billah Nagoudi, AbdelRahim A. Elmadany, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan:
A Benchmark Study of Contrastive Learning for Arabic Social Meaning. CoRR abs/2210.12314 (2022) - [i35]Md Tawkat Islam Khondaker, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan:
Cross-Platform and Cross-Domain Abusive Language Detection with Supervised Contrastive Learning. CoRR abs/2211.06452 (2022) - [i34]Yuxi Feng, Xiaoyuan Yi, Xiting Wang, Laks V. S. Lakshmanan, Xing Xie:
DuNST: Dual Noisy Self Training for Semi-Supervised Controllable Text Generation. CoRR abs/2212.08724 (2022) - 2021
- [j66]Chenhao Ma, Yixiang Fang, Reynold Cheng, Laks V. S. Lakshmanan, Wenjie Zhang, Xuemin Lin:
Efficient Directed Densest Subgraph Discovery. SIGMOD Rec. 50(1): 33-40 (2021) - [j65]Chenhao Ma, Yixiang Fang, Reynold Cheng, Laks V. S. Lakshmanan, Wenjie Zhang, Xuemin Lin:
On Directed Densest Subgraph Discovery. ACM Trans. Database Syst. 46(4): 13:1-13:45 (2021) - [c166]Ganesh Jawahar, El Moatez Billah Nagoudi, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan:
Exploring Text-to-Text Transformers for English to Hinglish Machine Translation with Synthetic Code-Mixing. CALCS@NAACL 2021: 36-46 - [c165]Gorisha Agarwal, Laks V. S. Lakshmanan, Xiaoming Gao, Kevin Ventullo, Saurav Mohapatra, Saikat Basu:
MAYUR: Map conflAtion using earlY prUning and Rank join. SIGSPATIAL/GIS 2021: 550-553 - [c164]Prithu Banerjee, Lingyang Chu, Yong Zhang, Laks V. S. Lakshmanan, Lanjun Wang:
Stealthy Targeted Data Poisoning Attack on Knowledge Graphs. ICDE 2021: 2069-2074 - [c163]Kai Han, Benwei Wu, Jing Tang, Shuang Cui, Çigdem Aslay, Laks V. S. Lakshmanan:
Efficient and Effective Algorithms for Revenue Maximization in Social Advertising. SIGMOD Conference 2021: 671-684 - [c162]Saravanan Thirumuruganathan, Michael Simpson, Laks V. S. Lakshmanan:
To Intervene or Not To Intervene: Cost based Intervention for Combating Fake News. SIGMOD Conference 2021: 2300-2309 - [i33]Ganesh Jawahar, El Moatez Billah Nagoudi, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan:
Exploring Text-to-Text Transformers for English to Hinglish Machine Translation with Synthetic Code-Mixing. CoRR abs/2105.08807 (2021) - [i32]Kai Han, Benwei Wu, Jing Tang, Shuang Cui, Çigdem Aslay, Laks V. S. Lakshmanan:
Efficient and Effective Algorithms for Revenue Maximization in Social Advertising. CoRR abs/2107.04997 (2021) - 2020
- [j64]Prithu Banerjee, Laks V. S. Lakshmanan, Wei Chen:
Maximizing Social Welfare in a Competitive Diffusion Model. Proc. VLDB Endow. 14(4): 613-625 (2020) - [j63]Anthony-Alexander Christidis, Laks V. S. Lakshmanan, Ezequiel Smucler, Ruben H. Zamar:
Split Regularized Regression. Technometrics 62(3): 330-338 (2020) - [j62]Behrooz Omidvar-Tehrani, Sihem Amer-Yahia, Laks V. S. Lakshmanan:
Cohort analytics: efficiency and applicability. VLDB J. 29(6): 1527-1550 (2020) - [c161]Sarah Elhammadi, Laks V. S. Lakshmanan, Raymond T. Ng, Michael Simpson, Baoxing Huai, Zhefeng Wang, Lanjun Wang:
A High Precision Pipeline for Financial Knowledge Graph Construction. COLING 2020: 967-977 - [c160]Ganesh Jawahar, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan:
Automatic Detection of Machine Generated Text: A Critical Survey. COLING 2020: 2296-2309 - [c159]Alexandra Kim, Laks V. S. Lakshmanan, Divesh Srivastava:
Summarizing Hierarchical Multidimensional Data. ICDE 2020: 877-888 - [c158]Chenhao Ma, Yixiang Fang, Reynold Cheng, Laks V. S. Lakshmanan, Wenjie Zhang, Xuemin Lin:
Efficient Algorithms for Densest Subgraph Discovery on Large Directed Graphs. SIGMOD Conference 2020: 1051-1066 - [c157]Tobias Grubenmann, Reynold C. K. Cheng, Laks V. S. Lakshmanan:
TSA: A Truthful Mechanism for Social Advertising. WSDM 2020: 214-222 - [i31]Ganesh Jawahar, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan:
Automatic Detection of Machine Generated Text: A Critical Survey. CoRR abs/2011.01314 (2020) - [i30]Prithu Banerjee, Wei Chen, Laks V. S. Lakshmanan:
Maximizing Social Welfare in a Competitive Diffusion Model. CoRR abs/2012.03354 (2020)
2010 – 2019
- 2019
- [b2]Xin Huang, Laks V. S. Lakshmanan, Jianliang Xu:
Community Search over Big Graphs. Synthesis Lectures on Data Management, Morgan & Claypool Publishers 2019, ISBN 978-3-031-00746-0 - [j61]Yixiang Fang, Kaiqiang Yu, Reynold Cheng, Laks V. S. Lakshmanan, Xuemin Lin:
Efficient Algorithms for Densest Subgraph Discovery. Proc. VLDB Endow. 12(11): 1719-1732 (2019) - [j60]Laks V. S. Lakshmanan, Michael Simpson, Saravanan Thirumuruganathan:
Combating Fake News: A Data Management and Mining Perspective. Proc. VLDB Endow. 12(12): 1990-1993 (2019) - [j59]Chenhao Ma, Reynold Cheng, Laks V. S. Lakshmanan, Tobias Grubenmann, Yixiang Fang, Xiaodong Li:
LINC: A Motif Counting Algorithm for Uncertain Graphs. Proc. VLDB Endow. 13(2): 155-168 (2019) - [c156]Prithu Banerjee, Wei Chen, Laks V. S. Lakshmanan:
Maximizing Welfare in Social Networks under A Utility Driven Influence Diffusion model. SIGMOD Conference 2019: 1078-1095 - [c155]Jing Tang, Keke Huang, Xiaokui Xiao, Laks V. S. Lakshmanan, Xueyan Tang, Aixin Sun, Andrew Lim:
Efficient Approximation Algorithms for Adaptive Seed Minimization. SIGMOD Conference 2019: 1096-1113 - [r3]Laks V. S. Lakshmanan, Panayiotis Tsaparas, Yuichi Yoshida:
Influence Analytics in Graphs. Encyclopedia of Big Data Technologies 2019 - [i29]Yixiang Fang, Kaiqiang Yu, Reynold Cheng, Laks V. S. Lakshmanan, Xuemin Lin:
Efficient Algorithms for Densest Subgraph Discovery. CoRR abs/1906.00341 (2019) - [i28]Jing Tang, Keke Huang, Xiaokui Xiao, Laks V. S. Lakshmanan, Xueyan Tang, Aixin Sun, Andrew Lim:
Efficient Approximation Algorithms for Adaptive Seed Minimization. CoRR abs/1907.09668 (2019) - 2018
- [c154]Behrooz Omidvar-Tehrani, Sihem Amer-Yahia, Laks V. S. Lakshmanan:
Cohort Representation and Exploration. DSAA 2018: 169-178 - [c153]Dmitri V. Kalashnikov, Laks V. S. Lakshmanan, Divesh Srivastava:
FastQRE: Fast Query Reverse Engineering. SIGMOD Conference 2018: 337-350 - [c152]Çigdem Aslay, Laks V. S. Lakshmanan, Wei Lu, Xiaokui Xiao:
Influence Maximization in Online Social Networks. WSDM 2018: 775-776 - [r2]Laks V. S. Lakshmanan:
XML Tree Pattern, XML Twig Query. Encyclopedia of Database Systems (2nd ed.) 2018 - [i27]Prithu Banerjee, Wei Chen, Laks V. S. Lakshmanan:
EPIC: Welfare Maximization under Economically Postulated Independent Cascade Model. CoRR abs/1807.02502 (2018) - 2017
- [j58]Keke Huang, Sibo Wang, Glenn S. Bevilacqua, Xiaokui Xiao, Laks V. S. Lakshmanan:
Revisiting the Stop-and-Stare Algorithms for Influence Maximization. Proc. VLDB Endow. 10(9): 913-924 (2017) - [j57]Xin Huang, Laks V. S. Lakshmanan:
Attribute-Driven Community Search. Proc. VLDB Endow. 10(9): 949-960 (2017) - [j56]Çigdem Aslay, Francesco Bonchi, Laks V. S. Lakshmanan, Wei Lu:
Revenue Maximization in Incentivized Social Advertising. Proc. VLDB Endow. 10(11): 1238-1249 (2017) - [c151]Sharan Vaswani, Mark Schmidt, Laks V. S. Lakshmanan:
Horde of Bandits using Gaussian Markov Random Fields. AISTATS 2017: 690-699 - [c150]Xin Huang, Laks V. S. Lakshmanan, Jianliang Xu:
Community Search over Big Graphs: Models, Algorithms, and Opportunities. ICDE 2017: 1451-1454 - [c149]Sharan Vaswani, Branislav Kveton, Zheng Wen, Mohammad Ghavamzadeh, Laks V. S. Lakshmanan, Mark Schmidt:
Model-Independent Online Learning for Influence Maximization. ICML 2017: 3530-3539 - [c148]Sihem Amer-Yahia, Sofia Kleisarchaki, Naresh Kumar Kolloju, Laks V. S. Lakshmanan, Ruben H. Zamar:
Exploring Rated Datasets with Rating Maps. WWW 2017: 1411-1419 - [i26]Sampoorna Biswas, Laks V. S. Lakshmanan, Senjuti Basu Roy:
Combating the Cold Start User Problem in Model Based Collaborative Filtering. CoRR abs/1703.00397 (2017) - [i25]Sharan Vaswani, Branislav Kveton, Zheng Wen, Mohammad Ghavamzadeh, Laks V. S. Lakshmanan, Mark Schmidt:
Diffusion Independent Semi-Bandit Influence Maximization. CoRR abs/1703.00557 (2017) - [i24]Sharan Vaswani, Mark Schmidt, Laks V. S. Lakshmanan:
Horde of Bandits using Gaussian Markov Random Fields. CoRR abs/1703.02626 (2017) - [i23]Wei Lu, Xiaokui Xiao, Amit Goyal, Keke Huang, Laks V. S. Lakshmanan:
Refutations on "Debunking the Myths of Influence Maximization: An In-Depth Benchmarking Study". CoRR abs/1705.05144 (2017) - 2016
- [j55]Senjuti Basu Roy, Kostas Stefanidis, Georgia Koutrika, Laks V. S. Lakshmanan, Mirek Riedewald:
Report on the Third International Workshop on Exploratory Search in Databases and the Web (ExploreDB 2016). SIGMOD Rec. 45(3): 35-38 (2016) - [c147]Pei Lee, Laks V. S. Lakshmanan:
Query-Driven Maximum Quasi-Clique Search. SDM 2016: 522-530 - [c146]Laks V. S. Lakshmanan:
Viral marketing 2.0. NDA@SIGMOD 2016: 2:1 - [c145]Theodore Johnson, Yaron Kanza, Laks V. S. Lakshmanan, Vladislav Shkapenyuk:
Nepal: a path query language for communication networks. NDA@SIGMOD 2016: 6:1-6:8 - [c144]Xin Huang, Wei Lu, Laks V. S. Lakshmanan:
Truss Decomposition of Probabilistic Graphs: Semantics and Algorithms. SIGMOD Conference 2016: 77-90 - [e7]Senjuti Basu Roy, Kostas Stefanidis, Georgia Koutrika, Mirek Riedewald, Laks V. S. Lakshmanan:
Proceedings of the Third International Workshop on Exploratory Search in Databases and the Web, San Francisco, CA, USA, July 1, 2016. ACM 2016, ISBN 978-1-4503-4312-1 [contents] - [i22]Sharan Vaswani, Laks V. S. Lakshmanan:
Adaptive Influence Maximization in Social Networks: Why Commit when You can Adapt? CoRR abs/1604.08171 (2016) - [i21]Xin Huang, Laks V. S. Lakshmanan:
Attribute Truss Community Search. CoRR abs/1609.00090 (2016) - [i20]Çigdem Aslay, Francesco Bonchi, Laks V. S. Lakshmanan, Wei Lu:
Revenue Maximization in Incentivized Social Advertising. CoRR abs/1612.00531 (2016) - 2015
- [j54]Çigdem Aslay, Wei Lu, Francesco Bonchi, Amit Goyal, Laks V. S. Lakshmanan:
Viral Marketing Meets Social Advertising: Ad Allocation with Minimum Regret. Proc. VLDB Endow. 8(7): 822-833 (2015) - [j53]Wei Lu, Wei Chen, Laks V. S. Lakshmanan:
From Competition to Complementarity: Comparative Influence Diffusion and Maximization. Proc. VLDB Endow. 9(2): 60-71 (2015) - [j52]Xin Huang, Laks V. S. Lakshmanan, Jeffrey Xu Yu, Hong Cheng:
Approximate Closest Community Search in Networks. Proc. VLDB Endow. 9(4): 276-287 (2015) - [j51]Georgia Koutrika, Laks V. S. Lakshmanan, Mirek Riedewald, Mohamed A. Sharaf, Kostas Stefanidis:
Report on the Second International Workshop on Exploratory Search in Databases and the Web (ExploreDB 2015). SIGMOD Rec. 44(4): 49-52 (2015) - [c143]Senjuti Basu Roy, Laks V. S. Lakshmanan, Rui Liu:
From Group Recommendations to Group Formation. SIGMOD Conference 2015: 1603-1616 - [c142]Laks V. S. Lakshmanan:
Social Network Analytics: Beyond the Obvious. Big-O(Q)/DMAH@VLDB 2015: 149-154 - [e6]Georgia Koutrika, Laks V. S. Lakshmanan, Mirek Riedewald, Kostas Stefanidis:
Proceedings of the Second International Workshop on Exploratory Search in Databases and the Web, ExploreDB 2015, Melbourne, VIC, Australia, May 31 - June 04, 2015. ACM 2015, ISBN 978-1-4503-3740-3 [contents] - [i19]Sharan Vaswani, Laks V. S. Lakshmanan:
Influence Maximization with Bandits. CoRR abs/1503.00024 (2015) - [i18]Senjuti Basu Roy, Laks V. S. Lakshmanan, Rui Liu:
From Group Recommendations to Group Formation. CoRR abs/1503.03753 (2015) - [i17]Xin Huang, Laks V. S. Lakshmanan, Jeffrey Xu Yu, Hong Cheng:
Approximate Closest Community Search in Networks. CoRR abs/1505.05956 (2015) - [i16]Wei Lu, Wei Chen, Laks V. S. Lakshmanan:
From Competition to Complementarity: Comparative Influence Diffusion and Maximization. CoRR abs/1507.00317 (2015) - 2014
- [j50]Wei Lu, Shanshan Chen, Keqian Li, Laks V. S. Lakshmanan:
Show Me the Money: Dynamic Recommendations for Revenue Maximization. Proc. VLDB Endow. 7(14): 1785-1796 (2014) - [j49]Min Xie, Laks V. S. Lakshmanan, Peter T. Wood:
Generating Top-k Packages via Preference Elicitation. Proc. VLDB Endow. 7(14): 1941-1952 (2014) - [j48]Georgia Koutrika, Laks V. S. Lakshmanan, Mirek Riedewald, Kostas Stefanidis:
Report on the First International Workshop on Exploratory Search in Databases and the Web (ExploreDB 2014). SIGMOD Rec. 43(2): 49-52 (2014) - [c141]Pei Lee, Laks V. S. Lakshmanan, Evangelos E. Milios:
CAST: A Context-Aware Story-Teller for Streaming Social Content. CIKM 2014: 789-798 - [c140]