| Empower sequence labeling with task-aware neural language model L Liu, J Shang, X Ren, F Xu, H Gui, J Peng, J Han Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 457 | 2018 |
| Network a/b testing: From sampling to estimation H Gui, Y Xu, A Bhasin, J Han Proceedings of the 24th International Conference on World Wide Web, 399-409, 2015 | 182 | 2015 |
| AspEm: Embedding Learning by Aspects in Heterogeneous Information Networks Y Shi, H Gui, Q Zhu, L Kaplan, J Han Proceedings of the 2018 SIAM International Conference on Data Mining, 144-152, 2018 | 120 | 2018 |
| Large-scale embedding learning in heterogeneous event data H Gui, J Liu, F Tao, M Jiang, B Norick, J Han 2016 IEEE 16th International Conference on Data Mining (ICDM), 907-912, 2016 | 108 | 2016 |
| Heterogeneous supervision for relation extraction: A representation learning approach L Liu, X Ren, Q Zhu, S Zhi, H Gui, H Ji, J Han Proceedings of the 2017 Conference on Empirical Methods in Natural Language …, 2017 | 87 | 2017 |
| Embedding learning with events in heterogeneous information networks H Gui, J Liu, F Tao, M Jiang, B Norick, L Kaplan, J Han IEEE transactions on knowledge and data engineering 29 (11), 2428-2441, 2017 | 61 | 2017 |
| Robust tensor decomposition with gross corruption Q Gu, H Gui, J Han Advances in Neural Information Processing Systems 27, 2014 | 52 | 2014 |
| Modeling topic diffusion in multi-relational bibliographic information networks H Gui, Y Sun, J Han, G Brova Proceedings of the 23rd ACM international conference on conference on …, 2014 | 45 | 2014 |
| Towards faster rates and oracle property for low-rank matrix estimation H Gui, Q Gu, J Han Proceedings of the 33rd International Conference on International Conference …, 2015 | 32 | 2015 |
| Prep: Path-based relevance from a probabilistic perspective in heterogeneous information networks Y Shi, PW Chan, H Zhuang, H Gui, J Han Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge …, 2017 | 31 | 2017 |
| Expert finding in heterogeneous bibliographic networks with locally-trained embeddings H Gui, Q Zhu, L Liu, A Zhang, J Han arXiv preprint arXiv:1803.03370, 2018 | 18 | 2018 |
| Sampling of users in network a/b testing H Gui, Y Xu, A Bhasin, J Han US Patent App. 14/632,344, 2016 | 17 | 2016 |
| Bias correction and estimation in network a/b testing H Gui, Y Xu, A Bhasin, J Han US Patent App. 14/632,360, 2016 | 11 | 2016 |
| Wikidata Vandalism Detection-The Loganberry Vandalism Detector at WSDM Cup 2017 Q Zhu, H Ng, L Liu, Z Ji, B Jiang, J Shen, H Gui arXiv preprint arXiv:1712.06922, 2017 | 7 | 2017 |
| Downside management in recommender systems H Gui, H Liu, X Meng, A Bhasin, J Han 2016 IEEE/ACM International Conference on Advances in Social Networks …, 2016 | 6 | 2016 |
| Integrating Knowledge from Latent and Explicit Features for Triple Scoring-Team Radicchio's Triple Scorer at WSDM Cup 2017 LW Chen, B Mangipudi, J Bandlamudi, R Sehgal, Y Hao, M Jiang, H Gui arXiv preprint arXiv:1712.08357, 2017 | 2 | 2017 |
| LEVI: Generalizable Fine-tuning via Layer-wise Ensemble of Different Views Y Roh, Q Liu, H Gui, Z Yuan, Y Tang, SE Whang, L Liu, S Bi, L Hong, ... arXiv preprint arXiv:2402.04644, 2024 | 1 | 2024 |
| Hiformer: Heterogeneous Feature Interactions Learning with Transformers for Recommender Systems H Gui, R Wang, K Yin, L Jin, M Kula, T Xu, L Hong, EH Chi arXiv preprint arXiv:2311.05884, 2023 | 1 | 2023 |
| Knowledge Distillation Training via Encoded Information Exchange to Generate Models Structured for More Efficient Compute Z Zhao, H Gui, Q Liu, EH Chi, L Hong, B An US Patent App. 18/667,973, 2024 | | 2024 |
| Talking Models: Distill Pre-trained Knowledge to Downstream Models via Interactive Communication Z Zhao, Q Liu, H Gui, B An, L Hong, EH Chi arXiv preprint arXiv:2310.03188, 2023 | | 2023 |
Jiawei HanAbel Bliss Professor of Computer Science, University of IllinoisDirección de correo verificada de cs.uiuc.edu