Laks V. S. Lakshmanan

ORCID

Publication Activity (10 Years)

Years Active: 1991-2024
Publications (10 Years): 95

Top Venues

Publications

Yuxi Feng, Laks V. S. Lakshmanan
DuRE: Dual Contrastive Self Training for Semi-Supervised Relation Extraction. NAACL-HLT (2024)
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 (2024)
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 (2024)
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)
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)
Md Tawkat Islam Khondaker, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan
GreenLLaMA: A Framework for Detoxification with Explanations. CoRR (2024)
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 (2024)
Bin Xiang, Bogdan Cautis, Xiaokui Xiao, Olga Mula, Dusit Niyato, Laks V. S. Lakshmanan
Predicting Cascading Failures with a Hyperparametric Diffusion Model. CoRR (2024)
Bin Xiang, Bogdan Cautis, Xiaokui Xiao, Olga Mula, Dusit Niyato, Laks V. S. Lakshmanan
Predicting Cascading Failures with a Hyperparametric Diffusion Model. KDD (2024)
Ganesh Jawahar, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan, Dujian Ding
LLM Performance Predictors are good initializers for Architecture Search. ACL (Findings) (2024)
Dujian Ding, Bicheng Xu, Laks V. S. Lakshmanan
OCCAM: Towards Cost-Efficient and Accuracy-Aware Image Classification Inference. CoRR (2024)
Rudra Ranajee Saha, Laks V. S. Lakshmanan, Raymond T. Ng
Stance Detection with Explanations. Comput. Linguistics 50 (1) (2024)
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) (2024)
Prithu Banerjee, Wei Chen, Laks V. S. Lakshmanan
Mitigating Filter Bubbles Under a Competitive Diffusion Model. Proc. ACM Manag. Data 1 (2) (2023)
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 (2023)
Ganesh Jawahar, Subhabrata Mukherjee, Debadeepta Dey, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan, Caio Mendes, Gustavo de Rosa, Shital Shah
Small Character Models Match Large Word Models for Autocomplete Under Memory Constraints. SustaiNLP (2023)
Md Tawkat Islam Khondaker, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan
PACT: Pretraining with Adversarial Contrastive Learning for Text Classification. IJCNLP (1) (2023)
Yuxi Feng, Xiaoyuan Yi, Laks V. S. Lakshmanan, Xing Xie
KEST: Kernel Distance Based Efficient Self-Training for Improving Controllable Text Generation. CoRR (2023)
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) (2023)
Yuxi Feng, Xiaoyuan Yi, Laks V. S. Lakshmanan, Xing Xie
KEST: Kernel Distance Based Efficient Self-Training for Improving Controllable Text Generation. IJCAI (2023)
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)
Ganesh Jawahar, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan, Dujian Ding
LLM Performance Predictors are good initializers for Architecture Search. CoRR (2023)
Wensheng Luo, Chenhao Ma, Yixiang Fang, Laks V. S. Lakshmanan
A Survey of Densest Subgraph Discovery on Large Graphs. CoRR (2023)
Arkaprava Saha, Xiangyu Ke, Arijit Khan, Laks V. S. Lakshmanan
Voting-based Opinion Maximization. ICDE (2023)
Yuxi Feng, Xiaoyuan Yi, Xiting Wang, Laks V. S. Lakshmanan, Xing Xie
DuNST: Dual Noisy Self Training for Semi-Supervised Controllable Text Generation. CoRR (2022)
Ganesh Jawahar, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan
Automatic Detection of Entity-Manipulated Text using Factual Knowledge. CoRR (2022)
Arkaprava Saha, Xiangyu Ke, Arijit Khan, Laks V. S. Lakshmanan
Voting-based Opinion Maximization. CoRR (2022)
Glenn S. Bevilacqua, Laks V. S. Lakshmanan
A fractional memory-efficient approach for online continuous-time influence maximization. VLDB J. 31 (2) (2022)
Ali Behrouz, Farnoosh Hashemi, Laks V. S. Lakshmanan
FirmTruss Community Search in Multilayer Networks. Proc. VLDB Endow. 16 (3) (2022)
Laks V. S. Lakshmanan
Mid-Career Researcher, huh?: What just Changed? SIGMOD Rec. 51 (4) (2022)
Dujian Ding, Sihem Amer-Yahia, Laks V. S. Lakshmanan
On Efficient Approximate Queries over Machine Learning Models. Proc. VLDB Endow. 16 (4) (2022)
Farnoosh Hashemi, Ali Behrouz, Laks V. S. Lakshmanan
FirmCore Decomposition of Multilayer Networks. CoRR (2022)
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 (2022)
Michael Simpson, Farnoosh Hashemi, Laks V. S. Lakshmanan
Misinformation Mitigation under Differential Propagation Rates and Temporal Penalties. CoRR (2022)
Ganesh Jawahar, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan
Automatic Detection of Entity-Manipulated Text using Factual Knowledge. ACL (2) (2022)
Michael Simpson, Laks V. S. Lakshmanan, Farnoosh Hashemi
Misinformation Mitigation under Differential Propagation Rates and Temporal Penalties. Proc. VLDB Endow. 15 (10) (2022)
Chenhao Ma, Reynold Cheng, Laks V. S. Lakshmanan, Xiaolin Han
Finding Locally Densest Subgraphs: A Convex Programming Approach. Proc. VLDB Endow. 15 (11) (2022)
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)
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)
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 (2022)
Ali Behrouz, Farnoosh Hashemi, Laks V. S. Lakshmanan
FirmTruss Community Search in Multilayer Networks. CoRR (2022)
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 (2022)
Farnoosh Hashemi, Ali Behrouz, Laks V. S. Lakshmanan
FirmCore Decomposition of Multilayer Networks. WWW (2022)
Laks V. S. Lakshmanan
On a Quest for Combating Filter Bubbles and Misinformation. SIGMOD Conference (2022)
Dujian Ding, Sihem Amer-Yahia, Laks V. S. Lakshmanan
On Efficient Approximate Queries over Machine Learning Models. CoRR (2022)
Md Tawkat Islam Khondaker, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan
Cross-Platform and Cross-Domain Abusive Language Detection with Supervised Contrastive Learning. CoRR (2022)
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)
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)
Saravanan Thirumuruganathan, Michael Simpson, Laks V. S. Lakshmanan
To Intervene or Not To Intervene: Cost based Intervention for Combating Fake News. SIGMOD Conference (2021)
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) (2021)
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 (2021)
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 (2021)
Chenhao Ma, Yixiang Fang, Reynold Cheng, Laks V. S. Lakshmanan, Wenjie Zhang, Xuemin Lin
Efficient Directed Densest Subgraph Discovery. SIGMOD Rec. 50 (1) (2021)
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)
Prithu Banerjee, Lingyang Chu, Yong Zhang, Laks V. S. Lakshmanan, Lanjun Wang
Stealthy Targeted Data Poisoning Attack on Knowledge Graphs. ICDE (2021)
Anthony-Alexander Christidis, Laks V. S. Lakshmanan, Ezequiel Smucler, Ruben H. Zamar
Split Regularized Regression. Technometrics 62 (3) (2020)
Prithu Banerjee, Laks V. S. Lakshmanan, Wei Chen
Maximizing Social Welfare in a Competitive Diffusion Model. Proc. VLDB Endow. 14 (4) (2020)
Behrooz Omidvar-Tehrani, Sihem Amer-Yahia, Laks V. S. Lakshmanan
Cohort analytics: efficiency and applicability. VLDB J. 29 (6) (2020)
Ganesh Jawahar, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan
Automatic Detection of Machine Generated Text: A Critical Survey. COLING (2020)
Tobias Grubenmann, Reynold C. K. Cheng, Laks V. S. Lakshmanan
TSA: A Truthful Mechanism for Social Advertising. WSDM (2020)
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)
Prithu Banerjee, Wei Chen, Laks V. S. Lakshmanan
Maximizing Social Welfare in a Competitive Diffusion Model. CoRR (2020)
Ganesh Jawahar, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan
Automatic Detection of Machine Generated Text: A Critical Survey. CoRR (2020)
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)
Alexandra Kim, Laks V. S. Lakshmanan, Divesh Srivastava
Summarizing Hierarchical Multidimensional Data. ICDE (2020)
Yixiang Fang, Kaiqiang Yu, Reynold Cheng, Laks V. S. Lakshmanan, Xuemin Lin
Efficient Algorithms for Densest Subgraph Discovery. Proc. VLDB Endow. 12 (11) (2019)
Jing Tang, Keke Huang, Xiaokui Xiao, Laks V. S. Lakshmanan, Xueyan Tang, Aixin Sun, Andrew Lim
Efficient Approximation Algorithms for Adaptive Seed Minimization. CoRR (2019)
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) (2019)
Yixiang Fang, Kaiqiang Yu, Reynold Cheng, Laks V. S. Lakshmanan, Xuemin Lin
Efficient Algorithms for Densest Subgraph Discovery. CoRR (2019)
Laks V. S. Lakshmanan, Michael Simpson, Saravanan Thirumuruganathan
Combating Fake News: A Data Management and Mining Perspective. Proc. VLDB Endow. 12 (12) (2019)
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)
Prithu Banerjee, Wei Chen, Laks V. S. Lakshmanan
Maximizing Welfare in Social Networks under A Utility Driven Influence Diffusion model. SIGMOD Conference (2019)
Prithu Banerjee, Wei Chen, Laks V. S. Lakshmanan
EPIC: Welfare Maximization under Economically Postulated Independent Cascade Model. CoRR (2018)
Behrooz Omidvar-Tehrani, Sihem Amer-Yahia, Laks V. S. Lakshmanan
Cohort Representation and Exploration. DSAA (2018)
Çigdem Aslay, Laks V. S. Lakshmanan, Wei Lu, Xiaokui Xiao
Influence Maximization in Online Social Networks. WSDM (2018)
Dmitri V. Kalashnikov, Laks V. S. Lakshmanan, Divesh Srivastava
FastQRE: Fast Query Reverse Engineering. SIGMOD Conference (2018)
Sharan Vaswani, Branislav Kveton, Zheng Wen, Mohammad Ghavamzadeh, Laks V. S. Lakshmanan, Mark Schmidt
Model-Independent Online Learning for Influence Maximization. ICML (2017)
Xin Huang, Laks V. S. Lakshmanan
Attribute-Driven Community Search. Proc. VLDB Endow. 10 (9) (2017)
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 (2017)
Sihem Amer-Yahia, Sofia Kleisarchaki, Naresh Kumar Kolloju, Laks V. S. Lakshmanan, Ruben H. Zamar
Exploring Rated Datasets with Rating Maps. WWW (2017)
Sharan Vaswani, Branislav Kveton, Zheng Wen, Mohammad Ghavamzadeh, Laks V. S. Lakshmanan, Mark Schmidt
Diffusion Independent Semi-Bandit Influence Maximization. CoRR (2017)
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) (2017)
Sampoorna Biswas, Laks V. S. Lakshmanan, Senjuti Basu Roy
Combating the Cold Start User Problem in Model Based Collaborative Filtering. CoRR (2017)
Sharan Vaswani, Mark Schmidt, Laks V. S. Lakshmanan
Horde of Bandits using Gaussian Markov Random Fields. CoRR (2017)
Sharan Vaswani, Mark Schmidt, Laks V. S. Lakshmanan
Horde of Bandits using Gaussian Markov Random Fields. AISTATS (2017)
Xin Huang, Laks V. S. Lakshmanan, Jianliang Xu
Community Search over Big Graphs: Models, Algorithms, and Opportunities. ICDE (2017)
Çigdem Aslay, Francesco Bonchi, Laks V. S. Lakshmanan, Wei Lu
Revenue Maximization in Incentivized Social Advertising. Proc. VLDB Endow. 10 (11) (2017)
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) (2016)
Çigdem Aslay, Francesco Bonchi, Laks V. S. Lakshmanan, Wei Lu
Revenue Maximization in Incentivized Social Advertising. CoRR (2016)
Sharan Vaswani, Laks V. S. Lakshmanan
Adaptive Influence Maximization in Social Networks: Why Commit when You can Adapt? CoRR (2016)
Pei Lee, Laks V. S. Lakshmanan
Query-Driven Maximum Quasi-Clique Search. SDM (2016)
Theodore Johnson, Yaron Kanza, Laks V. S. Lakshmanan, Vladislav Shkapenyuk
Nepal: a path query language for communication networks. NDA@SIGMOD (2016)
Xin Huang, Wei Lu, Laks V. S. Lakshmanan
Truss Decomposition of Probabilistic Graphs: Semantics and Algorithms. SIGMOD Conference (2016)
Laks V. S. Lakshmanan
Viral marketing 2.0. NDA@SIGMOD (2016)
Xin Huang, Laks V. S. Lakshmanan
Attribute Truss Community Search. CoRR (2016)
Senjuti Basu Roy, Laks V. S. Lakshmanan, Rui Liu
From Group Recommendations to Group Formation. SIGMOD Conference (2015)
Wei Lu, Wei Chen, Laks V. S. Lakshmanan
From Competition to Complementarity: Comparative Influence Diffusion and Maximization. Proc. VLDB Endow. 9 (2) (2015)
Wei Lu, Wei Chen, Laks V. S. Lakshmanan
From Competition to Complementarity: Comparative Influence Diffusion and Maximization. CoRR (2015)
Laks V. S. Lakshmanan
Social Network Analytics: Beyond the Obvious. Big-O(Q)/DMAH@VLDB (2015)
Xin Huang, Laks V. S. Lakshmanan, Jeffrey Xu Yu, Hong Cheng
Approximate Closest Community Search in Networks. Proc. VLDB Endow. 9 (4) (2015)

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Publication Activity (10 Years)

Top Topics

Top Venues

Laks V. S. Lakshmanan