Huan Gui
Huan Gui
Google DeepMind
Verified email at - Homepage
Cited by
Cited by
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
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
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
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
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
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
Robust tensor decomposition with gross corruption
Q Gu, H Gui, J Han
Advances in Neural Information Processing Systems 27, 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
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
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
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
Sampling of users in network a/b testing
H Gui, Y Xu, A Bhasin, J Han
US Patent App. 14/632,344, 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
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
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
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
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
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
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
De facto diagnosis specialties: R ecognition and discovery
A Zhang, X Lu, CA Gunter, S Yao, F Tao, R Zhu, H Gui, D Fabbri, ...
Learning Health Systems 2 (3), e10057, 2018
The system can't perform the operation now. Try again later.
Articles 1–20