default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDLaks V. S. Lakshmanan
V. S. Lakshmanan 0001
Person information
- affiliation: University of British Columbia, Department of Computer Science
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
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) - [c183]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 - [c182]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 - [c181]Md Tawkat Islam Khondaker, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan:
DetoxLLM: A Framework for Detoxification with Explanations. EMNLP 2024: 19112-19139 - [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 - [i55]Md Tawkat Islam Khondaker, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan:
GreenLLaMA: A Framework for Detoxification with Explanations. CoRR abs/2402.15951 (2024) - [i54]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) - [i53]Dujian Ding, Bicheng Xu, Laks V. S. Lakshmanan:
OCCAM: Towards Cost-Efficient and Accuracy-Aware Image Classification Inference. CoRR abs/2406.04508 (2024) - [i52]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) - [i51]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) - [i50]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) - [i49]Xiang Zhang, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan:
Autoregressive + Chain of Thought = Recurrent: Recurrence's Role in Language Models' Computability and a Revisit of Recurrent Transformer. CoRR abs/2409.09239 (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]Vincent Yun Lou, Smriti Bhagat, Laks V. S. Lakshmanan, Sharan Vaswani:
Modeling non-progressive phenomena for influence propagation. COSN 2014: 131-138 - [c139]Rui Chen, Min Xie, Laks V. S. Lakshmanan:
Thwarting Passive Privacy Attacks in Collaborative Filtering. DASFAA (2) 2014: 218-233 - [c138]Georgia Koutrika, Laks V. S. Lakshmanan, Mirek Riedewald, Kostas Stefanidis:
Exploratory Search in Databases and the Web. EDBT/ICDT Workshops 2014: 158-159 - [c137]Laks V. S. Lakshmanan, Alex Thomo:
View-Based Tree-Language Rewritings for XML. FoIKS 2014: 270-289 - [c136]Pei Lee, Laks V. S. Lakshmanan, Evangelos E. Milios:
Incremental cluster evolution tracking from highly dynamic network data. ICDE 2014: 3-14 - [c135]Wei Lu, Stratis Ioannidis, Smriti Bhagat, Laks V. S. Lakshmanan:
Optimal recommendations under attraction, aversion, and social influence. KDD 2014: 811-820 - [c134]Keqian Li, Wei Lu, Smriti Bhagat, Laks V. S. Lakshmanan, Cong Yu:
On social event organization. KDD 2014: 1206-1215 - [c133]Pei Lee, Laks V. S. Lakshmanan, Mitul Tiwari, Sam Shah:
Modeling impression discounting in large-scale recommender systems. KDD 2014: 1837-1846 - [c132]Yidan Liu, Min Xie, Laks V. S. Lakshmanan:
Recommending user generated item lists. RecSys 2014: 185-192 - [c131]Vignesh Veppur Sankaranarayanan, Junaed Sattar, Laks V. S. Lakshmanan:
Auto-play: A Data Mining Approach to ODI Cricket Simulation and Prediction. SDM 2014: 1064-1072 - [i15]Vincent Yun Lou, Smriti Bhagat, Laks V. S. Lakshmanan, Sharan Vaswani:
Modeling Non-Progressive Phenomena for Influence Propagation. CoRR abs/1408.6466 (2014) - [i14]Wei Lu, Shanshan Chen, Keqian Li, Laks V. S. Lakshmanan:
Show Me the Money: Dynamic Recommendations for Revenue Maximization. CoRR abs/1409.0080 (2014) - [i13]Çigdem Aslay, Wei Lu, Francesco Bonchi, Amit Goyal, Laks V. S. Lakshmanan:
Viral Marketing Meets Social Advertising: Ad Allocation with Minimum Regret. CoRR abs/1412.1462 (2014) - 2013
- [b1]Wei Chen, Laks V. S. Lakshmanan, Carlos Castillo:
Information and Influence Propagation in Social Networks. Synthesis Lectures on Data Management, Morgan & Claypool Publishers 2013, ISBN 9781627051156, pp. 1-177 - [j47]Leopoldo E. Bertossi, Solmaz Kolahi, Laks V. S. Lakshmanan:
Data Cleaning and Query Answering with Matching Dependencies and Matching Functions. Theory Comput. Syst. 52(3): 441-482 (2013) - [j46]Min Xie, Laks V. S. Lakshmanan, Peter T. Wood:
IPS: An Interactive Package Configuration System for Trip Planning. Proc. VLDB Endow. 6(12): 1362-1365 (2013) - [j45]Fosca Giannotti, Laks V. S. Lakshmanan, Anna Monreale, Dino Pedreschi, Wendy Hui Wang:
Privacy-Preserving Mining of Association Rules From Outsourced Transaction Databases. IEEE Syst. J. 7(3): 385-395 (2013) - [j44]Amit Goyal, Francesco Bonchi, Laks V. S. Lakshmanan, Suresh Venkatasubramanian:
On minimizing budget and time in influence propagation over social networks. Soc. Netw. Anal. Min. 3(2): 179-192 (2013) - [c130]Min Xie, Laks V. S. Lakshmanan, Peter T. Wood:
Efficient top-k query answering using cached views. EDBT 2013: 489-500 - [c129]Glenn S. Bevilacqua, Shealen Clare, Amit Goyal, Laks V. S. Lakshmanan:
Validating Network Value of Influencers by Means of Explanations. ICDM 2013: 967-972 - [c128]Wei Lu, Francesco Bonchi, Amit Goyal, Laks V. S. Lakshmanan:
The bang for the buck: fair competitive viral marketing from the host perspective. KDD 2013: 928-936 - [c127]Pei Lee, Laks V. S. Lakshmanan, Evangelos E. Milios:
KeySee: supporting keyword search on evolving events in social streams. KDD 2013: 1478-1481 - [c126]Zeinab Abbassi, Laks V. S. Lakshmanan, Min Xie:
Fair Recommendations for Online Barter Exchange Networks. WebDB 2013: 43-48 - [c125]Mohsen Jamali, Laks V. S. Lakshmanan:
HeteroMF: recommendation in heterogeneous information networks using context dependent factor models. WWW 2013: 643-654 - [i12]Glenn S. Bevilacqua, Shealen Clare, Amit Goyal, Laks V. S. Lakshmanan:
Validating Network Value of Influencers by means of Explanations. CoRR abs/1310.5430 (2013) - [i11]Pei Lee, Laks V. S. Lakshmanan, Evangelos E. Milios:
Event Evolution Tracking from Streaming Social Posts. CoRR abs/1311.5978 (2013) - 2012
- [j43]Min Xie, Laks V. S. Lakshmanan, Peter T. Wood:
Composite recommendations: from items to packages. Frontiers Comput. Sci. 6(3): 264-277 (2012) - [j42]Francesco Bonchi, Pooya Esfandiar, David F. Gleich, Chen Greif, Laks V. S. Lakshmanan:
Fast Matrix Computations for Pairwise and Columnwise Commute Times and Katz Scores. Internet Math. 8(1-2): 73-112 (2012) - [c124]Tianyu Li, Pirooz Chubak, Laks V. S. Lakshmanan, Rachel Pottinger:
Efficient extraction of ontologies from domain specific text corpora. CIKM 2012: 1537-1541 - [c123]Pei Lee, Laks V. S. Lakshmanan, Jeffrey Xu Yu:
On Top-k Structural Similarity Search. ICDE 2012: 774-785 - [c122]Wei Lu, Laks V. S. Lakshmanan:
Profit Maximization over Social Networks. ICDM 2012: 479-488 - [c121]Amit Goyal, Laks V. S. Lakshmanan:
RecMax: exploiting recommender systems for fun and profit. KDD 2012: 1294-1302 - [c120]Zeinab Bahmani, Leopoldo E. Bertossi, Solmaz Kolahi, Laks V. S. Lakshmanan:
Declarative Entity Resolution via Matching Dependencies and Answer Set Programs. KR 2012 - [c119]Fosca Giannotti, Laks V. S. Lakshmanan, Anna Monreale, Dino Pedreschi, Wendy Hui Wang:
Privacy-preserving Mining of Association Rules from Outsourced Transaction Databases. SEBD 2012: 233-242 - [c118]Smriti Bhagat, Amit Goyal, Laks V. S. Lakshmanan:
Maximizing product adoption in social networks. WSDM 2012: 603-612 - [e5]Silvana Castano, Panos Vassiliadis, Laks V. S. Lakshmanan, Mong-Li Lee:
Advances in Conceptual Modeling - ER 2012 Workshops CMS, ECDM-NoCoDA, MoDIC, MORE-BI, RIGiM, SeCoGIS, WISM, Florence, Italy, October 15-18, 2012. Proceedings. Lecture Notes in Computer Science 7518, Springer 2012, ISBN 978-3-642-33998-1 [contents] - [i10]Wei Lu, Laks V. S. Lakshmanan:
Profit Maximization over Social Networks. CoRR abs/1210.4211 (2012) - 2011
- [j41]Mohammad Khabbaz, Min Xie, Laks V. S. Lakshmanan:
TopRecs+: Pushing the Envelope on Recommender Systems. IEEE Data Eng. Bull. 34(2): 61-68 (2011) - [j40]Min Xie, Laks V. S. Lakshmanan, Peter T. Wood:
Efficient Rank Join with Aggregation Constraints. Proc. VLDB Endow. 4(11): 1201-1212 (2011) - [j39]Amit Goyal, Francesco Bonchi, Laks V. S. Lakshmanan:
A Data-Based Approach to Social Influence Maximization. Proc. VLDB Endow. 5(1): 73-84 (2011) - [j38]Francesco Bonchi, Laks V. S. Lakshmanan, Wendy Hui Wang:
Trajectory anonymity in publishing personal mobility data. SIGKDD Explor. 13(1): 30-42 (2011) - [c117]Ali Moosavi, Tianyu Li, Laks V. S. Lakshmanan, Rachel Pottinger:
ONTECTAS: Bridging the Gap between Collaborative Tagging Systems and Structured Data. CAiSE 2011: 436-451 - [c116]Xueyao Liang, Min Xie, Laks V. S. Lakshmanan:
Adding structure to top-k: from items to expansions. CIKM 2011: 1699-1708 - [c115]Mohammad Khabbaz, Laks V. S. Lakshmanan:
TopRecs: Top-k algorithms for item-based collaborative filtering. EDBT 2011: 213-224 - [c114]Min Xie, Laks V. S. Lakshmanan, Peter T. Wood:
CompRec-Trip: A composite recommendation system for travel planning. ICDE 2011: 1352-1355 - [c113]Amit Goyal, Wei Lu, Laks V. S. Lakshmanan:
SIMPATH: An Efficient Algorithm for Influence Maximization under the Linear Threshold Model. ICDM 2011: 211-220 - [c112]Leopoldo E. Bertossi, Solmaz Kolahi, Laks V. S. Lakshmanan:
Data cleaning and query answering with matching dependencies and matching functions. ICDT 2011: 268-279 - [c111]Su Chen, Xin Luna Dong, Laks V. S. Lakshmanan, Divesh Srivastava:
We challenge you to certify your updates. SIGMOD Conference 2011: 481-492 - [c110]Amit Goyal, Wei Lu, Laks V. S. Lakshmanan:
CELF++: optimizing the greedy algorithm for influence maximization in social networks. WWW (Companion Volume) 2011: 47-48 - [p2]Fosca Giannotti, Laks V. S. Lakshmanan, Anna Monreale, Dino Pedreschi, Wendy Hui Wang:
Privacy-Preserving Data Mining from Outsourced Databases. Computers, Privacy and Data Protection 2011: 411-426 - [i9]Francesco Bonchi, Pooya Esfandiar, David F. Gleich, Chen Greif, Laks V. S. Lakshmanan:
Fast matrix computations for pair-wise and column-wise commute times and Katz scores. CoRR abs/1104.3791 (2011) - [i8]Amit Goyal, Francesco Bonchi, Laks V. S. Lakshmanan:
A Data-Based Approach to Social Influence Maximization. CoRR abs/1109.6886 (2011) - [i7]Mohammad Khabbaz, Smriti Bhagat, Laks V. S. Lakshmanan:
Finding Heavy Paths in Graphs: A Rank Join Approach. CoRR abs/1112.1117 (2011) - 2010
- [j37]Andrea Calì, Laks V. S. Lakshmanan, Davide Martinenghi:
Selected papers from the Logic in Databases Workshop 2008. J. Appl. Log. 8(2): 151-152 (2010) - [j36]Angela Bonifati, Elaine Qing Chang, Terence Ho, Laks V. S. Lakshmanan, Rachel Pottinger, Yongik Chung:
Schema mapping and query translation in heterogeneous P2P XML databases. VLDB J. 19(2): 231-256 (2010) - [j35]Klemens Böhm, Laks V. S. Lakshmanan:
Foreword. VLDB J. 19(6): 759-760 (2010) - [c109]Solmaz Kolahi, Laks V. S. Lakshmanan:
Exploiting Conflict Structures in Inconsistent Databases. ADBIS 2010: 320-335 - [c108]Min Xie, Laks V. S. Lakshmanan, Peter T. Wood:
Breaking out of the box of recommendations: from items to packages. RecSys 2010: 151-158 - [c107]Pooya Esfandiar, Francesco Bonchi, David F. Gleich, Chen Greif, Laks V. S. Lakshmanan, Byung-Won On:
Fast Katz and Commuters: Efficient Estimation of Social Relatedness in Large Networks. WAW 2010: 132-145 - [c106]Amit Goyal, Francesco Bonchi, Laks V. S. Lakshmanan:
Learning influence probabilities in social networks. WSDM 2010: 241-250 - [e4]Alberto H. F. Laender, Laks V. S. Lakshmanan:
Proceedings of the 4th Alberto Mendelzon International Workshop on Foundations of Data Management, Buenos Aires, Argentina, May 17-20, 2010. CEUR Workshop Proceedings 619, CEUR-WS.org 2010 [contents] - [i6]Amit Goyal, Francesco Bonchi, Laks V. S. Lakshmanan:
Approximation Analysis of Influence Spread in Social Networks. CoRR abs/1008.2005 (2010) - [i5]Leopoldo E. Bertossi, Solmaz Kolahi, Laks V. S. Lakshmanan:
Data Cleaning and Query Answering with Matching Dependencies and Matching Functions. CoRR abs/1008.3743 (2010)
2000 – 2009
- 2009
- [j34]Sihem Amer-Yahia, Laks V. S. Lakshmanan, Sergei Vassilvitskii, Cong Yu:
Battling Predictability and Overconcentration in Recommender Systems. IEEE Data Eng. Bull. 32(4): 33-40 (2009) - [j33]Andrea Calì, Laks V. S. Lakshmanan, Davide Martinenghi:
Logic in databases: report on the LID 2008 workshop. SIGMOD Rec. 38(3): 44-49 (2009) - [j32]Zhenjie Zhang, Laks V. S. Lakshmanan, Anthony K. H. Tung:
On domination game analysis for microeconomic data mining. ACM Trans. Knowl. Discov. Data 2(4): 18:1-18:27 (2009) - [c105]Sihem Amer-Yahia, Laks V. S. Lakshmanan, Cong Yu:
SocialScope: Enabling Information Discovery on Social Content Sites. CIDR 2009 - [c104]Roman Yarovoy, Francesco Bonchi, Laks V. S. Lakshmanan, Wendy Hui Wang:
Anonymizing moving objects: how to hide a MOB in a crowd? EDBT 2009: 72-83 - [c103]Cong Yu, Laks V. S. Lakshmanan, Sihem Amer-Yahia:
It takes variety to make a world: diversification in recommender systems. EDBT 2009: 368-378 - [c102]Zeinab Abbassi, Laks V. S. Lakshmanan:
On Efficient Recommendations for Online Exchange Markets. ICDE 2009: 712-723 - [c101]Wenfei Fan, Floris Geerts, Laks V. S. Lakshmanan, Ming Xiong:
Discovering Conditional Functional Dependencies. ICDE 2009: 1231-1234 - [c100]Cong Yu, Laks V. S. Lakshmanan, Sihem Amer-Yahia:
Recommendation Diversification Using Explanations. ICDE 2009: 1299-1302 - [c99]Amit Goyal, Byung-Won On, Francesco Bonchi, Laks V. S. Lakshmanan:
GuruMine: A Pattern Mining System for Discovering Leaders and Tribes. ICDE 2009: 1471-1474 - [c98]Solmaz Kolahi, Laks V. S. Lakshmanan:
On approximating optimum repairs for functional dependency violations. ICDT 2009: 53-62 - [c97]Zeinab Abbassi, Sihem Amer-Yahia, Laks V. S. Lakshmanan, Sergei Vassilvitskii, Cong Yu:
Getting recommender systems to think outside the box. RecSys 2009: 285-288 - [r1]Laks V. S. Lakshmanan:
XML Tree Pattern, XML Twig Query. Encyclopedia of Database Systems 2009: 3637-3640 - [i4]Sihem Amer-Yahia, Laks V. S. Lakshmanan, Cong Yu:
SocialScope: Enabling Information Discovery on Social Content Sites. CoRR abs/0909.2058 (2009) - 2008
- [j31]Sihem Amer-Yahia, Michael Benedikt, Laks V. S. Lakshmanan, Julia Stoyanovich:
Efficient network aware search in collaborative tagging sites. Proc. VLDB Endow. 1(1): 710-721 (2008) - [j30]Laks V. S. Lakshmanan, Raymond T. Ng, Ganesh Ramesh:
On disclosure risk analysis of anonymized itemsets in the presence of prior knowledge. ACM Trans. Knowl. Discov. Data 2(3): 13:1-13:44 (2008) - [c96]Amit Goyal, Francesco Bonchi, Laks V. S. Lakshmanan:
Discovering leaders from community actions. CIKM 2008: 499-508 - [c95]Laks V. S. Lakshmanan, Alexander Russakovsky, Vaishnavi Sashikanth:
What-if OLAP Queries with Changing Dimensions. ICDE 2008: 1334-1336 - [c94]Zeinab Abbassi, Laks V. S. Lakshmanan:
Offline matching approximation algorithms in exchange markets. WWW 2008: 1187-1188 - [i3]Irini Fundulaki, Sihem Amer-Yahia, Laks V. S. Lakshmanan:
Personalizing XML Full Text Search in PIMENTO. Ranked XML Querying 2008 - 2007
- [c93]Chaitanya Gokhale, Nitin Gupta, Pranav Kumar, Laks V. S. Lakshmanan, Raymond T. Ng, B. Aditya Prakash:
Complex Group-By Queries for XML. ICDE 2007: 646-655 - [c92]Shaofeng Bu, Laks V. S. Lakshmanan, Raymond T. Ng, Ganesh Ramesh:
Preservation Of Patterns and Input-Output Privacy. ICDE 2007: 696-705 - [c91]Sihem Amer-Yahia, Irini Fundulaki, Laks V. S. Lakshmanan:
Personalizing XML Search in PIMENTO. ICDE 2007: 906-915 - [c90]Nuwee Wiwatwattana, H. V. Jagadish, Laks V. S. Lakshmanan, Divesh Srivastava:
X3: A Cube Operator for XML OLAP. ICDE 2007: 916-925 - [p1]Wendy Hui Wang, Divesh Srivastava, Laks V. S. Lakshmanan, SungRan Cho, Sihem Amer-Yahia:
Optimizing Tree Pattern Queries over Secure XML Databases. Secure Data Management in Decentralized Systems 2007: 127-165 - 2006
- [j29]Jian Pei, Jiawei Han, Laks V. S. Lakshmanan:
An Erratum on "Pushing Convertible Constraints in Frequent Itemset Mining". Data Min. Knowl. Discov. 12(1): 119 (2006) - [j28]Toon Calders, Laks V. S. Lakshmanan, Raymond T. Ng, Jan Paredaens:
Expressive power of an algebra for data mining. ACM Trans. Database Syst. 31(4): 1169-1214 (2006) - [c89]Nuwee Wiwatwattana, H. V. Jagadish, Laks V. S. Lakshmanan, Divesh Srivastava:
Making Designer Schemas with Colors. ICDE 2006: 15 - [c88]Wendy Hui Wang, Laks V. S. Lakshmanan:
Efficient Secure Query Evaluation over Encrypted XML Databases. VLDB 2006: 127-138 - [c87]Laks V. S. Lakshmanan, Wendy Hui Wang, Zheng (Jessica) Zhao:
Answering Tree Pattern Queries Using Views. VLDB 2006: 571-582 - [c86]Wendy Hui Wang, Laks V. S. Lakshmanan:
Probabilistic privacy analysis of published views. WPES 2006: 81-84 - [e3]Laks V. S. Lakshmanan, Prasan Roy, Anthony K. H. Tung:
Proceedings of the 13th International Conference on Management of Data, December 14-16, 2006, Delhi, India. Tata McGraw-Hill Publishing Company Limited 2006, ISBN 0-07-063374-6 [contents] - 2005
- [c85]Laks V. S. Lakshmanan, Raymond T. Ng, Ganesh Ramesh:
To Do or Not To Do: The Dilemma of Disclosing Anonymized Data. SIGMOD Conference 2005: 61-72 - [c84]Shaofeng Bu, Laks V. S. Lakshmanan, Raymond T. Ng:
MDL Summarization with Holes. VLDB 2005: 433-444 - [c83]Angela Bonifati, Elaine Qing Chang, Terence Ho, Laks V. S. Lakshmanan, Rachel Pottinger:
HePToX: Marrying XML and Heterogeneity in Your P2P Databases. VLDB 2005: 1267-1270 - [c82]Sihem Amer-Yahia, Irini Fundulaki, Prateek Jain, Laks V. S. Lakshmanan:
Personalizing XML Text Search in PimenT. VLDB 2005: 1310-1313 - [i2]Angela Bonifati, Elaine Qing Chang, Terence Ho, Laks V. S. Lakshmanan:
HepToX: Heterogeneous Peer to Peer XML Databases. CoRR abs/cs/0506002 (2005) - 2004
- [j27]Jian Pei, Jiawei Han, Laks V. S. Lakshmanan:
Pushing Convertible Constraints in Frequent Itemset Mining. Data Min. Knowl. Discov. 8(3): 227-252 (2004) - [j26]Ruth Yuee Zhang, Laks V. S. Lakshmanan, Ruben H. Zamar:
Extracting relational data from HTML repositories. SIGKDD Explor. 6(2): 5-13 (2004) - [j25]Ting Yu, Divesh Srivastava, Laks V. S. Lakshmanan, H. V. Jagadish:
A compressed accessibility map for XML. ACM Trans. Database Syst. 29(2): 363-402 (2004) - [c81]Stelios Paparizos, Yuqing Wu, Laks V. S. Lakshmanan, H. V. Jagadish:
Tree Logical Classes for Efficient Evaluation of XQuery. SIGMOD Conference 2004: 71-82 - [c80]Sihem Amer-Yahia, Laks V. S. Lakshmanan, Shashank Pandit:
FleXPath: Flexible Structure and Full-Text Querying for XML. SIGMOD Conference 2004: 83-94 - [c79]H. V. Jagadish, Laks V. S. Lakshmanan, Monica Scannapieco, Divesh Srivastava, Nuwee Wiwatwattana:
Colorful XML: One Hierarchy Isn't Enough. SIGMOD Conference 2004: 251-262 - [c78]Laks V. S. Lakshmanan, Ganesh Ramesh, Wendy Hui Wang, Zheng (Jessica) Zhao:
On Testing Satisfiability of Tree Pattern Queries. VLDB 2004: 120-131 - 2003
- [j24]Laks V. S. Lakshmanan, Fereidoon Sadri:
Information Integration and the Semantic Web. IEEE Data Eng. Bull. 26(4): 19-25 (2003) - [j23]Michael O. Akinde, Michael H. Böhlen, Theodore Johnson, Laks V. S. Lakshmanan, Divesh Srivastava:
Efficient OLAP query processing in distributed data warehouses. Inf. Syst. 28(1-2): 111-135 (2003) - [j22]Laks V. S. Lakshmanan, Carson Kai-Sang Leung, Raymond T. Ng:
Efficient dynamic mining of constrained frequent sets. ACM Trans. Database Syst. 28(4): 337-389 (2003) - [c77]Ke Wang, Yuelong Jiang, Laks V. S. Lakshmanan:
Mining unexpected rules by pushing user dynamics. KDD 2003: 246-255 - [c76]Laks V. S. Lakshmanan, Fereidoon Sadri:
Interoperability on XML Data. ISWC 2003: 146-163 - [c75]Laks V. S. Lakshmanan, Jian Pei, Yan Zhao:
QC-Trees: An Efficient Summary Structure for Semantic OLAP. SIGMOD Conference 2003: 64-75 - [c74]Laks V. S. Lakshmanan, Jian Pei, Yan Zhao:
SOCQET: Semantic OLAP with Compressed Cube and Summarization. SIGMOD Conference 2003: 658 - [c73]SungRan Cho, Sihem Amer-Yahia, Laks V. S. Lakshmanan, Divesh Srivastava:
LockX: A System for Efficiently Querying Secure XML. SIGMOD Conference 2003: 669 - [c72]Stelios Paparizos, Shurug Al-Khalifa, Adriane Chapman, H. V. Jagadish, Laks V. S. Lakshmanan, Andrew Nierman, Jignesh M. Patel, Divesh Srivastava, Nuwee Wiwatwattana, Yuqing Wu, Cong Yu:
TIMBER: A Native System for Querying XML. SIGMOD Conference 2003: 672 - [c71]Zhimin Chen, H. V. Jagadish, Laks V. S. Lakshmanan, Stelios Paparizos:
From Tree Patterns to Generalized Tree Patterns: On Efficient Evaluation of XQuery. VLDB 2003: 237-248 - [c70]Laks V. S. Lakshmanan, Jian Pei, Yan Zhao:
Efficacious Data Cube Exploration by Semantic Summarization and Compression. VLDB 2003: 1125-1128 - [c69]Laks V. S. Lakshmanan, Fereidoon Sadri:
XML Interoperability. WebDB 2003: 19-24 - [i1]Laks V. S. Lakshmanan, Fereidoon Sadri:
On A Theory of Probabilistic Deductive Databases. CoRR cs.DB/0312043 (2003) - 2002
- [j21]Carson Kai-Sang Leung, Laks V. S. Lakshmanan, Raymond T. Ng:
Exploiting succinct constraints using FP-trees. SIGKDD Explor. 4(1): 40-49 (2002) - [j20]H. V. Jagadish, Shurug Al-Khalifa, Adriane Chapman, Laks V. S. Lakshmanan, Andrew Nierman, Stelios Paparizos, Jignesh M. Patel, Divesh Srivastava, Nuwee Wiwatwattana, Yuqing Wu, Cong Yu:
TIMBER: A native XML database. VLDB J. 11(4): 274-291 (2002) - [j19]Sihem Amer-Yahia, SungRan Cho, Laks V. S. Lakshmanan, Divesh Srivastava:
Tree pattern query minimization. VLDB J. 11(4): 315-331 (2002) - [c68]Laks V. S. Lakshmanan, Sailaja Parthasarathy:
On Efficient Matching of Streaming XML Documents and Queries. EDBT 2002: 142-160 - [c67]Michael O. Akinde, Michael H. Böhlen, Theodore Johnson, Laks V. S. Lakshmanan, Divesh Srivastava:
Efficient OLAP Query Processing in Distributed Data Warehouses. EDBT 2002: 336-353 - [c66]Stelios Paparizos, Shurug Al-Khalifa, H. V. Jagadish, Laks V. S. Lakshmanan, Andrew Nierman, Divesh Srivastava, Yuqing Wu:
Grouping in XML. EDBT Workshops 2002: 128-147 - [c65]Michael O. Akinde, Michael H. Böhlen, Theodore Johnson, Laks V. S. Lakshmanan, Divesh Srivastava:
Efficient OLAP Query Processing in Distributed Data Warehouse. ICDE 2002: 262 - [c64]Ting Yu, Divesh Srivastava, Laks V. S. Lakshmanan, H. V. Jagadish:
Compressed Accessibility Map: Efficient Access Control for XML. VLDB 2002: 478-489 - [c63]SungRan Cho, Sihem Amer-Yahia, Laks V. S. Lakshmanan, Divesh Srivastava:
Optimizing the Secure Evaluation of Twig Queries. VLDB 2002: 490-501 - [c62]Laks V. S. Lakshmanan, Raymond T. Ng, Christine Xing Wang, Xiaodong Zhou, Theodore Johnson:
The Generalized MDL Approach for Summarization. VLDB 2002: 766-777 - [c61]Laks V. S. Lakshmanan, Jian Pei, Jiawei Han:
Quotient Cube: How to Summarize the Semantics of a Data Cube. VLDB 2002: 778-789 - [e2]Laks V. S. Lakshmanan:
Design and Management of Data Warehouses 2002, Proceedings of the 4th Intl. Workshop DMDW'2002, Toronto, Canada, May 27, 2002. CEUR Workshop Proceedings 58, CEUR-WS.org 2002 [contents] - 2001
- [j18]Kenneth A. Ross, James R. Hamilton, Laks V. S. Lakshmanan, Limsoon Wong:
Reminiscences on Influential Papers. SIGMOD Rec. 30(4): 90-91 (2001) - [j17]Laks V. S. Lakshmanan, Nematollaah Shiri:
A Parametric Approach to Deductive Databases with Uncertainty. IEEE Trans. Knowl. Data Eng. 13(4): 554-570 (2001) - [j16]Laks V. S. Lakshmanan, Fereidoon Sadri, Subbu N. Subramanian:
SchemaSQL: An extension to SQL for multidatabase interoperability. ACM Trans. Database Syst. 26(4): 476-519 (2001) - [j15]Laks V. S. Lakshmanan, Fereidoon Sadri:
On a theory of probabilistic deductive databases. Theory Pract. Log. Program. 1(1): 5-42 (2001) - [c60]H. V. Jagadish, Laks V. S. Lakshmanan, Divesh Srivastava, Keith Thompson:
TAX: A Tree Algebra for XML. DBPL 2001: 149-164 - [c59]Gösta Grahne, Laks V. S. Lakshmanan, Xiaohong Wang, Ming Hao Xie:
On Dual Mining: From Patterns to Circumstances, and Back. ICDE 2001: 195-204 - [c58]Jian Pei, Jiawei Han, Laks V. S. Lakshmanan:
Mining Frequent Item Sets with Convertible Constraints. ICDE 2001: 433-442 - [c57]Anthony K. H. Tung, Raymond T. Ng, Laks V. S. Lakshmanan, Jiawei Han:
Constraint-based clustering in large databases. ICDT 2001: 405-419 - [c56]Jiawei Han, Laks V. S. Lakshmanan, Jian Pei:
Scalable frequent-pattern mining methods: an overview. KDD Tutorials 2001 - [c55]Sihem Amer-Yahia, SungRan Cho, Laks V. S. Lakshmanan, Divesh Srivastava:
Minimization of Tree Pattern Queries. SIGMOD Conference 2001: 497-508 - 2000
- [j14]Laks V. S. Lakshmanan, Carson Kai-Sang Leung, Raymond T. Ng:
The Segment Support Map: Scalable Mining of Frequent Itemsets. SIGKDD Explor. 2(2): 21-27 (2000) - [c54]Sihem Amer-Yahia, H. V. Jagadish, Laks V. S. Lakshmanan, Divesh Srivastava:
On Bounding-Schemas for LDAP Directories. EDBT 2000: 287-301 - [c53]Gösta Grahne, Laks V. S. Lakshmanan, Xiaohong Wang:
Efficient Mining of Constrained Correlated Sets. ICDE 2000: 512-521 - [c52]Anthony K. H. Tung, Raymond T. Ng, Laks V. S. Lakshmanan, Jiawei Han:
Geo-Spatial Clustering with User-Specified Constraints. MDM/KDD 2000: 1-7 - [c51]Theodore Johnson, Laks V. S. Lakshmanan, Raymond T. Ng:
The 3W Model and Algebra for Unified Data Mining. VLDB 2000: 21-32
1990 – 1999
- 1999
- [j13]Jiawei Han, Laks V. S. Lakshmanan, Raymond T. Ng:
Constraint-Based Multidimensional Data Mining. Computer 32(8): 46-50 (1999) - [c50]Gösta Grahne, Laks V. S. Lakshmanan:
On the Difference between Navigating Semi-structured Data and Querying It. DBPL 1999: 271-296 - [c49]Gösta Grahne, Laks V. S. Lakshmanan, Xiaohong Wang:
Interactive Mining of Correlations - A Constraint Perspective. 1999 ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery 1999 - [c48]Theodore Johnson, Raymond T. Ng, Laks V. S. Lakshmanan:
Towards a Toolkit for Data Analysis and Mining. 1999 ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery 1999 - [c47]Devavrat Shah, Laks V. S. Lakshmanan, Krithi Ramamritham, S. Sudarshan:
Interestingness and Pruning of Mined Patterns. 1999 ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery 1999 - [c46]H. V. Jagadish, Laks V. S. Lakshmanan, Divesh Srivastava:
Snakes and Sandwiches: Optimal Clustering Strategies for a Data Warehouse. SIGMOD Conference 1999: 37-48 - [c45]H. V. Jagadish, Laks V. S. Lakshmanan, Tova Milo, Divesh Srivastava, Dimitra Vista:
Querying Network Directories. SIGMOD Conference 1999: 133-144 - [c44]Laks V. S. Lakshmanan, Raymond T. Ng, Jiawei Han, Alex Pang:
Optimization of Constrained Frequent Set Queries with 2-variable Constraints. SIGMOD Conference 1999: 157-168 - [c43]Raymond T. Ng, Laks V. S. Lakshmanan, Jiawei Han, Teresa Mah:
Exploratory Mining via Constrained Frequent Set Queries. SIGMOD Conference 1999: 556-558 - [c42]Laks V. S. Lakshmanan, Fereidoon Sadri, Subbu N. Subramanian:
On Efficiently Implementing SchemaSQL on an SQL Database System. VLDB 1999: 471-482 - [c41]H. V. Jagadish, Laks V. S. Lakshmanan, Divesh Srivastava:
What can Hierarchies do for Data Warehouses? VLDB 1999: 530-541 - 1998
- [j12]Raymond T. Ng, Jiawei Han, Laks V. S. Lakshmanan:
Editorial. Data Min. Knowl. Discov. 2(3): 231-232 (1998) - [c40]Laks V. S. Lakshmanan, Krishnaprasad Thirunarayan:
Declarative Frameworks for Inheritance. Logics for Databases and Information Systems 1998: 357-388 - [c39]Laks V. S. Lakshmanan, Subbu N. Subramanian, Nita Goyal, Ravi Krishnamurthy:
On Query Spreadsheets. ICDE 1998: 134-141 - [c38]Raymond T. Ng, Laks V. S. Lakshmanan, Jiawei Han, Alex Pang:
Exploratory Mining and Pruning Optimizations of Constrained Association Rules. SIGMOD Conference 1998: 13-24 - [c37]Frédéric Gingras, Laks V. S. Lakshmanan:
nD-SQL: A Multi-Dimensional Language for Interoperability and OLAP. VLDB 1998: 134-145 - 1997
- [j11]Laks V. S. Lakshmanan, Fereidoon Sadri:
Uncertain Deductive Databases: A Hybrid Approach. Inf. Syst. 22(8): 483-508 (1997) - [j10]Laks V. S. Lakshmanan, Fereidoon Sadri, Iyer N. Subramanian:
Logic and Algebraic Languages for Interoperability in Multidatabase Systems. J. Log. Program. 33(2): 101-149 (1997) - [j9]Laks V. S. Lakshmanan:
Preface. Theor. Comput. Sci. 171(1-2): 1-2 (1997) - [j8]Laks V. S. Lakshmanan, Nicola Leone, Robert B. Ross, V. S. Subrahmanian:
ProbView: A Flexible Probabilistic Database System. ACM Trans. Database Syst. 22(3): 419-469 (1997) - [c36]Frédéric Gingras, Laks V. S. Lakshmanan, Iyer N. Subramanian, Despina Papoulis, Nematollaah Shiri:
Languages for Multi-database Interoperability. SIGMOD Conference 1997: 536-538 - [c35]Marc Gyssens, Laks V. S. Lakshmanan:
A Foundation for Multi-dimensional Databases. VLDB 1997: 106-115 - 1996
- [c34]Alanoly Andrews, Nematollaah Shiri, Laks V. S. Lakshmanan, Iyer N. Subramanian:
On Implementing SchemaLog - A Database Programming Language. CIKM 1996: 309-316 - [c33]Laks V. S. Lakshmanan, Nematollaah Shiri:
A Parametric Approach to Deductive Databases with Uncertainty. Logic in Databases 1996: 61-81 - [c32]Marc Gyssens, Laks V. S. Lakshmanan, Iyer N. Subramanian:
Tables as a Paradigm for Querying and Restructuring. PODS 1996: 93-103 - [c31]Laks V. S. Lakshmanan, Fereidoon Sadri, Iyer N. Subramanian:
A Declarative Language for Querying and Restructuring the WEB. RIDE-NDS 1996: 12-21 - [c30]Laks V. S. Lakshmanan, Fereidoon Sadri, Iyer N. Subramanian:
SchemaSQL - A Language for Interoperability in Relational Multi-Database Systems. VLDB 1996: 239-250 - 1995
- [j7]Jiawei Han, Laks V. S. Lakshmanan:
Evaluation of Regular Nonlinear Recursions by Deductive Database Techniques. Inf. Syst. 20(5): 419-441 (1995) - [c29]Hasan M. Jamil, Laks V. S. Lakshmanan:
An Object-Oriented Front-end for Deductive Databases. AMAST 1995: 581-584 - [c28]Laks V. S. Lakshmanan, Iyer N. Subramanian, Despina Papoulis, Nematollaah Shiri:
A Declarative System for Multi-database Interoperability. AMAST 1995: 586-589 - [c27]Laks V. S. Lakshmanan, Rokia Missaoui:
Pushing Semantics Inside Recursion: A General Framework for Semantic Optimization of Recursive Queries. ICDE 1995: 211-220 - [c26]Hasan M. Jamil, Laks V. S. Lakshmanan:
A Declarative Semantics for Behavioral Inheritance and Conflict Resolution. ILPS 1995: 130-144 - 1994
- [j6]V. S. Lakshmanan:
On Three-Valued Autoepistemic Reasoning and the Semantics of Logic Programs. Methods Log. Comput. Sci. 1(1): 77-110 (1994) - [j5]Fangqing Dong, Laks V. S. Lakshmanan:
Intuitionistic Interpretation of Deductive Databases with Incomplete Information. Theor. Comput. Sci. 133(2): 267-306 (1994) - [c25]Laks V. S. Lakshmanan, Fereidoon Sadri:
Modeling Uncertainty in Deductive Databases. DEXA 1994: 724-733 - [c24]Laks V. S. Lakshmanan:
An Epistemic Foundation for Logic Programming with Uncertainty. FSTTCS 1994: 89-100 - [c23]Laks V. S. Lakshmanan, Fereidoon Sadri:
Probabilistic Deductive Databases. ILPS 1994: 254-268 - 1993
- [j4]N. Chandrasekharan, Laks V. S. Lakshmanan, Muralidhar Medidi:
Efficient Parallel Algorithms for Finding Chordless Cycles in Graphs. Parallel Process. Lett. 3: 165-170 (1993) - [c22]Laks V. S. Lakshmanan, Fereidoon Sadri, Iyer N. Subramanian:
On the Logical Foundations of Schema Integration and Evolution in Heterogeneous Database Systems. DOOD 1993: 81-100 - [c21]Laks V. S. Lakshmanan, Karima Ashraf, Jiawei Han:
Homomorphic Tree Embeddings and Their Applications to Recursive Program Optimization. LICS 1993: 344-353 - [c20]Fangqing Dong, Laks V. S. Lakshmanan:
Canonical Kripke Models and The Intuitonistic Semantics of Logic Programs (Extended Abstract). LPNMR 1993: 437-456 - [c19]Fangqing Dong, Laks V. S. Lakshmanan:
A Deductive Approach to Hypothetical Query Answering. ILPS 1993: 609-628 - [c18]Jiawei Han, Laks V. S. Lakshmanan:
Evaluation of Regular Nonlinear Recursive Programs. ILPS 1993: 648 - [c17]Laks V. S. Lakshmanan, Heather L. Johnstone:
A Relational Data Model for Manipulating Probabilistic Knowledge. SOFTEKS Workshop on Incompleteness and Uncertainty in Information Systems 1993: 138-152 - [c16]Laks V. S. Lakshmanan:
Evolution of Intelligent Database Systems: A Personal Perspective. SOFTEKS Workshop on Incompleteness and Uncertainty in Information Systems 1993: 189-208 - [e1]Vangalur S. Alagar, Laks V. S. Lakshmanan, Fereidoon Sadri:
Formal Methods in Databases and Software Engineering, Proceedings of the Workshop on Formal Methods in Databases and Software Engineering, Montreal, Canada, 15-16 May 1992. Workshops in Computing, Springer 1993, ISBN 3-540-19812-1 [contents] - 1992
- [j3]R. Govindarajan, Sheng Yu, V. S. Lakshmanan:
Attempting guards in parallel: A data flow approach to execute generalized guarded commands. Int. J. Parallel Program. 21(4): 225-268 (1992) - [c15]Laks V. S. Lakshmanan, Daniel A. Nonen:
On Querying Temporal Deductive Databases. Formal Methods in Databases and Software Engineering 1992: 158-174 - [c14]Fangqing Dong, Laks V. S. Lakshmanan:
Intuitionistic Interpretation of Deductive Databases with Incomplete Information. Formal Methods in Databases and Software Engineering 1992: 175-192 - [c13]Laks V. S. Lakshmanan, Daniel A. Nonen:
Superfiniteness of Query Answers in Deductive Databases: An Automata-Theoretic Approach. FSTTCS 1992: 176-190 - [c12]Laks V. S. Lakshmanan, Rokia Missaoui:
On Semantic Query Optimization in Deductive Databases. ICDE 1992: 368-375 - [c11]Fangqing Dong, Laks V. S. Lakshmanan:
Deductive Databases with Incomplete Information. JICSLP 1992: 303-317 - 1991
- [c10]V. S. Lakshmanan, C. H. Yim:
Can Filters do Magic for Deductive Databases? ALPUK 1991: 174-189 - [c9]Laks V. S. Lakshmanan, Héctor J. Hernández:
Structural Query Optimization - A uniform Framework for Semantic Query Optimization in Deductive Databases. PODS 1991: 102-114 - 1990
- [c8]V. S. Lakshmanan:
Autoepistemic Logic Revisited: The Bias-Free Stable Semantics. LPNMR 1990: 73-80
1980 – 1989
- 1989
- [c7]V. S. Lakshmanan:
Query Evaluation with Null Values: How Complex is Completeness? FSTTCS 1989: 204-222 - [c6]V. S. Lakshmanan, Alberto O. Mendelzon:
Inductive Pebble Games and the Expressive Power of Datalog. PODS 1989: 301-310 - 1988
- [j2]V. S. Lakshmanan:
Split-Freedom and MVD-Intersection: A New Characterization of Multivalued Dependencies Having Conflict-Free Covers. Theor. Comput. Sci. 62(1-2): 105-122 (1988) - 1987
- [j1]V. S. Lakshmanan, C. E. Veni Madhavan:
An Algebraic Theory of Functional and Multivalued Dependencies in Relational Databases. Theor. Comput. Sci. 54: 103-128 (1987) - [c5]Alessandro D'Atri, Paolino Di Felice, V. S. Lakshmanan, Marina Moscarini:
On Global Context Dependencies and their Properties. MFDBS 1987: 71-79 - 1986
- [c4]V. S. Lakshmanan, C. E. Veni Madhavan:
Binary Decompositions and Acyclic Schemes. FSTTCS 1986: 214-238 - [c3]V. S. Lakshmanan:
Split-Freedom and MVD-Intersection: A New Characterization of Multivalued Dependencies Having Conflict-Free Covers. ICDT 1986: 221-241 - 1985
- [c2]V. S. Lakshmanan, C. E. Veni Madhavan:
The Implication Problem for Functional and Multivalued Dependencies: An Algebraic Approach. FSTTCS 1985: 303-328 - 1984
- [c1]V. S. Lakshmanan, N. Chandrasekharan, C. E. Veni Madhavan:
Recognition and Top-Down Generation of beta-Acyclic Database Schemes. FSTTCS 1984: 344-366
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-11-15 19:33 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
