Trust the model when it is confident: Masked model-based actor-critic F Pan, J He, D Tu, Q He Advances in neural information processing systems 33, 10537-10546, 2020 | 37 | 2020 |
A general cross-domain recommendation framework via Bayesian neural network J He, R Liu, F Zhuang, F Lin, C Niu, Q He 2018 IEEE International Conference on Data Mining (ICDM), 1001-1006, 2018 | 29 | 2018 |
Collaborating between local and global learning for distributed online multiple tasks X Jin, P Luo, F Zhuang, J He, Q He Proceedings of the 24th ACM International on Conference on Information and …, 2015 | 22 | 2015 |
Bayesian dual neural networks for recommendation J He, F Zhuang, Y Liu, Q He, F Lin Frontiers of Computer Science 13, 1255-1265, 2019 | 12 | 2019 |
Online Bayesian Max-Margin Subspace Multi-View Learning. J He, C Du, F Zhuang, X Yin, Q He, G Long IJCAI, 1555-1561, 2016 | 11 | 2016 |
Online Bayesian max-margin subspace learning for multi-view classification and regression J He, C Du, F Zhuang, X Yin, Q He, G Long Machine Learning 109, 219-249, 2020 | 7 | 2020 |
Transfer learning with manifold regularized convolutional neural network F Zhuang, L Huang, J He, J Ma, Q He Knowledge Science, Engineering and Management: 10th International Conference …, 2017 | 5 | 2017 |
Generating Synergistic Formulaic Alpha Collections via Reinforcement Learning S Yu, H Xue, X Ao, F Pan, J He, D Tu, Q He Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 4 | 2023 |
Learn continuously, act discretely: Hybrid action-space reinforcement learning for optimal execution F Pan, T Zhang, L Luo, J He, S Liu arXiv preprint arXiv:2207.11152, 2022 | 4 | 2022 |
Nonlinear Maximum Margin Multi-View Learning with Adaptive Kernel. J He, C Du, C Du, F Zhuang, Q He, G Long IJCAI, 1830-1836, 2017 | 4 | 2017 |
Gradient-adaptive pareto optimization for constrained reinforcement learning Z Zhou, M Huang, F Pan, J He, X Ao, D Tu, Q He Proceedings of the AAAI Conference on Artificial Intelligence 37 (9), 11443 …, 2023 | 3 | 2023 |
Style miner: find significant and stable explanatory factors in time series with constrained reinforcement learning D Li, F Pan, J He, Z Xu, D Tu, G Fan arXiv preprint arXiv:2303.11716, 2023 | 3 | 2023 |
Knowledge triple mining via multi-task learning Z Zhang, F Zhuang, X Li, ZY Niu, J He, Q He, H Xiong Information Systems 80, 64-75, 2019 | 3 | 2019 |
Potential off-grid user prediction system based on Spark X LI, Y SUN, F ZHUANG, J HE, Z ZHANG, S ZHU, Q HE ZTE Communications 17 (2), 26, 2019 | 2 | 2019 |
Learning beyond predefined label space via bayesian nonparametric topic modelling C Du, F Zhuang, J He, Q He, G Long Machine Learning and Knowledge Discovery in Databases: European Conference …, 2016 | 1 | 2016 |
Page Layout Method and Apparatus J He, F Pan, X Jin, D Tu US Patent App. 18/360,497, 2023 | | 2023 |
Rethinking Pareto Approaches in Constrained Reinforcement Learning M Huang, F Pan, J He, X Ao, Q He | | 2021 |
CCA-Flow: Deep Multi-view Subspace Learning with Inverse Autoregressive Flow J He, F Pan, F Zhuang, Q He Asian Conference on Machine Learning, 177-192, 2020 | | 2020 |
Efficient and Adaptive Kernelization for Nonlinear Max-margin Multi-view Learning C Du, J He, C Du, F Zhuang, Q He, G Long arXiv preprint arXiv:1910.05250, 2019 | | 2019 |
Nonparametric Bayesian Multi-Task Large-margin Classification. C Du, J He, F Zhuang, Y Qi, Q He ECAI, 255-260, 2014 | | 2014 |