| Detecting malicious endpoints using network connectivity and flow information S Saha, L Liu, R Torres, J Xu, A Nucci US Patent 8,813,236, 2014 | 204 | 2014 |
| PURE: Positive-unlabeled recommendation with generative adversarial network Y Zhou, J Xu, J Wu, Z Taghavi, E Korpeoglu, K Achan, J He Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 47 | 2021 |
| FORMULA: FactORized MUlti-task LeArning for task discovery in personalized medical models J Xu, J Zhou, PN Tan 2015 SIAM International Conference on Data Mining (SDM15), 496-504, 2015 | 39 | 2015 |
| Online multi-task learning framework for ensemble forecasting J Xu, PN Tan, J Zhou, L Luo IEEE Transactions on Knowledge and Data Engineering 29 (6), 1268-1280, 2017 | 38 | 2017 |
| Multi-Task Feature Interaction Learning K Lin, J Xu, S Ji, J Zhou 2016 KDD, 2016 | 38 | 2016 |
| GSpartan: a Geospatio-Temporal Multi-task Learning Framework for Multi-location Prediction J Xu, PN Tan, L Luo, J Zhou 2016 SIAM International Conference on Data Mining (SDM16), 657-665, 2016 | 30 | 2016 |
| Detecting malicious clients in isp networks using http connectivity graph and flow information L Liu, S Saha, R Torres, J Xu, PN Tan, A Nucci, M Mellia 2014 IEEE/ACM International Conference on Advances in Social Networks …, 2014 | 27 | 2014 |
| ORION: Online Regularized multI-task regressiON and its application to ensemble forecasting J Xu, PN Tan, L Luo 2014 IEEE International Conference on Data Mining, 1061-1066, 2014 | 26 | 2014 |
| Llm-ensemble: Optimal large language model ensemble method for e-commerce product attribute value extraction C Fang, X Li, Z Fan, J Xu, K Nag, E Korpeoglu, S Kumar, K Achan arXiv preprint arXiv:2403.00863, 2024 | 23* | 2024 |
| Knowledge graph completion models are few-shot learners: An empirical study of relation labeling in e-commerce with llms J Chen, L Ma, X Li, N Thakurdesai, J Xu, JHD Cho, K Nag, E Korpeoglu, ... arXiv preprint arXiv:2305.09858, 2023 | 19 | 2023 |
| Spatio-temporal multi-task learning via tensor decomposition J Xu, J Zhou, PN Tan, X Liu, L Luo IEEE Transactions on Knowledge and Data Engineering 33 (6), 2764-2775, 2019 | 18 | 2019 |
| Synergies that Matter: Efficient Interaction Selection via Sparse Factorization Machine J Xu, K Lin, PN Tan, J Zhou 2016 SIAM International Conference on Data Mining (SDM16), 108-116, 2016 | 18 | 2016 |
| MUSCAT: Multi-Scale Spatio-Temporal Learning with Application to Climate Modeling. J Xu, X Liu, T Wilson, PN Tan, P Hatami, L Luo IJCAI, 2912-2918, 2018 | 16 | 2018 |
| LLM-take: theme-aware keyword extraction using large language models RY Maragheh, C Fang, CC Irugu, P Parikh, J Cho, J Xu, S Sukumar, ... 2023 IEEE International Conference on Big Data (BigData), 4318-4324, 2023 | 15 | 2023 |
| WISDOM: Weighted Incremental Spatio-Temporal Multi-Task Learning via Tensor Decomposition J Xu, J Zhou, PN Tan, X Liu, L Luo IEEE BigData 2016, 2016 | 14 | 2016 |
| Gan-based recommendation with positive-unlabeled sampling Y Zhou, J Xu, J Wu, ZT Nasrabadi, E Korpeoglu, K Achan, J He arXiv preprint arXiv:2012.06901, 2020 | 8 | 2020 |
| Llm-based aspect augmentations for recommendation systems RY Maragheh, L Morishetti, R Giahi, K Nag, J Xu, J Cho, E Korpeoglu, ... | 6 | 2023 |
| NEAT: a label noise-resistant complementary item recommender system with trustworthy evaluation L Ma, J Xu, JHD Cho, E Korpeoglu, S Kumar, K Achan 2021 IEEE International Conference on Big Data (Big Data), 469-479, 2021 | 6 | 2021 |
| Character-based Outfit Generation with Vision-augmented Style Extraction via LLMs N Forouzandehmehr, Y Cao, N Thakurdesai, R Giahi, L Ma, N Farrokhsiar, ... 2023 IEEE International Conference on Big Data (BigData), 1-7, 2023 | 4 | 2023 |
| LLMs with User-defined Prompts as Generic Data Operators for Reliable Data Processing L Ma, N Thakurdesai, J Chen, J Xu, E Korpeoglu, S Kumar, K Achan 2023 IEEE International Conference on Big Data (BigData), 3144-3148, 2023 | 4 | 2023 |
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