| Learning how to active learn: A deep reinforcement learning approach M Fang, Y Li, T Cohn Conference on Empirical Methods in Natural Language Processing, 2017 | 370 | 2017 |
| Iterative views agreement: An iterative low-rank based structured optimization method to multi-view spectral clustering Y Wang, W Zhang, L Wu, X Lin, M Fang, S Pan International Joint Conference on Artificial Intelligence, 2016 | 273 | 2016 |
| Liir: Learning individual intrinsic reward in multi-agent reinforcement learning Y Du, L Han, M Fang, J Liu, T Dai, D Tao Advances in Neural Information Processing Systems, 2019 | 205 | 2019 |
| Curriculum-guided hindsight experience replay M Fang, T Zhou, Y Du, L Han, Z Zhang Advances in Neural Information Processing Systems, 2019 | 190 | 2019 |
| Saliency propagation from simple to difficult C Gong, D Tao, W Liu, SJ Maybank, M Fang, K Fu, J Yang IEEE Conference on Computer Vision and Pattern Recognition, 2531-2539, 2015 | 177 | 2015 |
| Dual adversarial neural transfer for low-resource named entity recognition JT Zhou, H Zhang, D Jin, H Zhu, M Fang, RSM Goh, K Kwok Annual Meeting of the Association for Computational Linguistics, 3461-3471, 2019 | 128 | 2019 |
| Learning granularity-unified representations for text-to-image person re-identification Z Shao, X Zhang, M Fang, Z Lin, J Wang, C Ding Proceedings of the 30th acm international conference on multimedia, 5566-5574, 2022 | 121 | 2022 |
| Revisiting metric learning for few-shot image classification X Li, L Yu, CW Fu, M Fang, PA Heng Neurocomputing 406, 49-58, 2020 | 116 | 2020 |
| DHER: Hindsight experience replay for dynamic goals M Fang, C Zhou, B Shi, B Gong, J Xu, T Zhang International Conference on Learning Representations, 2018 | 110 | 2018 |
| Bag: Bi-directional attention entity graph convolutional network for multi-hop reasoning question answering Y Cao, M Fang, D Tao Annual Conference of the North American Chapter of the Association for …, 2019 | 107 | 2019 |
| Transfer hashing: From shallow to deep JT Zhou, H Zhao, X Peng, M Fang, Z Qin, RSM Goh IEEE Transactions on Neural Networks and Learning Systems 29 (12), 6191-6201, 2018 | 105 | 2018 |
| Reinforcement learning with multiple relational attention for solving vehicle routing problems Y Xu, M Fang, L Chen, G Xu, Y Du, C Zhang IEEE Transactions on Cybernetics 52 (10), 11107-11120, 2021 | 83 | 2021 |
| Active learning for crowdsourcing using knowledge transfer M Fang, J Yin, D Tao AAAI Conference on Artificial Intelligence 28 (1), 2014 | 82 | 2014 |
| Is Neural Topic Modelling Better than Clustering? An Empirical Study on Clustering with Contextual Embeddings for Topics Z Zhang, M Fang, L Chen, MR Namazi-Rad Annual Conference of the North American Chapter of the Association for …, 2022 | 81 | 2022 |
| Rethinking Goal-conditioned Supervised Learning and Its Connection to Offline RL R Yang, Y Lu, W Li, H Sun, M Fang, Y Du, X Li, L Han, C Zhang International Conference on Learning Representations, 2022 | 75 | 2022 |
| Model transfer for tagging low-resource languages using a bilingual dictionary M Fang, T Cohn Annual Meeting of the Association for Computational Linguistics, 2017 | 75 | 2017 |
| DAGN: Discourse-Aware Graph Network for Logical Reasoning Y Huang, M Fang, Y Cao, L Wang, X Liang Annual Conference of the North American Chapter of the Association for …, 2021 | 65 | 2021 |
| Enhancing the robustness of neural collaborative filtering systems under malicious attacks Y Du, M Fang, J Yi, C Xu, J Cheng, D Tao IEEE Transactions on Multimedia 21 (3), 555-565, 2018 | 60 | 2018 |
| Self-taught active learning from crowds M Fang, X Zhu, B Li, W Ding, X Wu IEEE International Conference on Data Mining, 858-863, 2012 | 56 | 2012 |
| Where would i go next? large language models as human mobility predictors X Wang, M Fang, Z Zeng, T Cheng arXiv preprint arXiv:2308.15197, 2023 | 53 | 2023 |
Dacheng TaoNanyang Technological Universityntu.edu.sg의 이메일 확인됨