Neural Personalized Ranking for Image Recommendation W Niu, J Caverlee, H Lu ACM International Conference on Web Search and Data Mining (WSDM '18), 2018 | 144 | 2018 |
Taper: A contextual tensor-based approach for personalized expert recommendation H Ge, J Caverlee, H Lu Proceedings of the 10th ACM Conference on Recommender Systems, 261-268, 2016 | 67 | 2016 |
Biaswatch: A lightweight system for discovering and tracking topic-sensitive opinion bias in social media H Lu, J Caverlee, W Niu Proceedings of the 24th ACM International on Conference on Information and …, 2015 | 64 | 2015 |
Quality-Aware Neural Complementary Item Recommendation Y Zhang, H Lu, W Niu, J Caverlee Proceedings of the 12th ACM Conference on Recommender Systems, 2018 | 58 | 2018 |
What are you known for? Learning user topical profiles with implicit and explicit footprints C Cao, H Ge, H Lu, X Hu, J Caverlee Proceedings of the 40th International ACM SIGIR Conference on Research and …, 2017 | 29 | 2017 |
Exploiting Geo-Spatial Preference for Personalized Expert Recommendation H Lu, J Caverlee Proceedings of the 9th ACM Conference on Recommender Systems, 67-74, 2015 | 25 | 2015 |
Large Language Models as Data Augmenters for Cold-Start Item Recommendation J Wang, H Lu, J Caverlee, EH Chi, M Chen Companion Proceedings of the ACM on Web Conference 2024, 726-729, 2024 | 19 | 2024 |
Discovering what you're known for: A contextual poisson factorization approach H Lu, J Caverlee, W Niu Proceedings of the 10th ACM Conference on Recommender Systems, 253-260, 2016 | 9 | 2016 |
Stochastic projective methods for simulating stiff chemical reacting systems H Lu, P Li Computer Physics Communications 183 (7), 1427-1442, 2012 | 9 | 2012 |
Linking brain behavior to underlying cellular mechanisms via large-scale brain modeling and simulation Y Zhang, B Yan, M Wang, J Hu, H Lu, P Li Neurocomputing 97, 317-331, 2012 | 7 | 2012 |
Learning Geo-Social User Topical Profiles with Bayesian Hierarchical User Factorization H Lu, W Niu, J Caverlee Procedding of the 41st International ACM SIGIR Conference on Research and …, 2018 | 4 | 2018 |
Location-Sensitive User Profiling Using Crowdsourced Labels W Niu, C James, H Lu The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18), 2018 | 4 | 2018 |
Fresh Content Recommendation at Scale: A Multi-funnel Solution and the Potential of LLMs J Wang, H Lu, M Chen Proceedings of the 17th ACM International Conference on Web Search and Data …, 2024 | 3 | 2024 |
Long-Term Value of Exploration: Measurements, Findings and Algorithms Y Su, X Wang, EY Le, L Liu, Y Li, H Lu, B Lipshitz, S Badam, L Heldt, S Bi, ... Proceedings of the 17th ACM International Conference on Web Search and Data …, 2024 | 3 | 2024 |
LLMs for User Interest Exploration in Large-scale Recommendation Systems J Wang*, H Lu*, Y Liu, H Ma, Y Wang, Y Gu, S Zhang, N Han, S Bi, ... Proceedings of the 18th ACM Conference on Recommender Systems, 872-877, 2024 | 2 | 2024 |
Value of exploration: Measurements, findings and algorithms Y Su, X Wang, EY Le, L Liu, Y Li, H Lu, B Lipshitz, S Badam, L Heldt, S Bi, ... CoRR, 2023 | 2 | 2023 |
Community-based geospatial tag estimation W Niu, J Caverlee, H Lu, K Kamath 2016 IEEE/ACM International Conference on Advances in Social Networks …, 2016 | 2 | 2016 |
Multi-Task Neural Linear Bandit for Exploration in Recommender Systems Y Su, H Lu, Y Li, L Liu, S Bi, EH Chi, M Chen Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and …, 2024 | 1 | 2024 |
Personalized Expert Recommendation: Models and Algorithms H Lu Texas A&M University, 2017 | 1 | 2017 |
LLMs for User Interest Exploration: A Hybrid Approach J Wang*, H Lu*, Y Liu, H Ma, Y Wang, Y Gu, S Zhang, S Bi, L Baugher, ... arXiv preprint arXiv:2405.16363, 2024 | | 2024 |