Adversarial attacks and defenses in images, graphs and text: A review H Xu, Y Ma, HC Liu, D Deb, H Liu, JL Tang, AK Jain International Journal of Automation and Computing 17, 151-178, 2020 | 470 | 2020 |
Optimal placement and configuration of roadside units in vehicular networks Y Liang, H Liu, D Rajan 2012 IEEE 75th Vehicular Technology Conference (VTC Spring), 1-6, 2012 | 115 | 2012 |
Does gender matter? towards fairness in dialogue systems H Liu, J Dacon, W Fan, H Liu, Z Liu, J Tang arXiv preprint arXiv:1910.10486, 2019 | 75 | 2019 |
Whole-chain recommendations X Zhao, L Xia, L Zou, H Liu, D Yin, J Tang Proceedings of the 29th ACM international conference on information …, 2020 | 59 | 2020 |
Autoemb: Automated embedding dimensionality search in streaming recommendations X Zhaok, H Liu, W Fan, H Liu, J Tang, C Wang, M Chen, X Zheng, X Liu, ... 2021 IEEE International Conference on Data Mining (ICDM), 896-905, 2021 | 57 | 2021 |
Dear: Deep reinforcement learning for online advertising impression in recommender systems X Zhao, C Gu, H Zhang, X Yang, X Liu, J Tang, H Liu Proceedings of the AAAI conference on artificial intelligence 35 (1), 750-758, 2021 | 52 | 2021 |
Mitigating gender bias for neural dialogue generation with adversarial learning H Liu, W Wang, Y Wang, H Liu, Z Liu, J Tang arXiv preprint arXiv:2009.13028, 2020 | 49 | 2020 |
Attacking black-box recommendations via copying cross-domain user profiles W Fan, T Derr, X Zhao, Y Ma, H Liu, J Wang, J Tang, Q Li 2021 IEEE 37th International Conference on Data Engineering (ICDE), 1583-1594, 2021 | 40 | 2021 |
A comprehensive survey on trustworthy graph neural networks: Privacy, robustness, fairness, and explainability E Dai, T Zhao, H Zhu, J Xu, Z Guo, H Liu, J Tang, S Wang arXiv preprint arXiv:2204.08570, 2022 | 29 | 2022 |
Autoloss: Automated loss function search in recommendations X Zhao, H Liu, W Fan, H Liu, J Tang, C Wang Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 28 | 2021 |
Memory-efficient embedding for recommendations X Zhao, H Liu, H Liu, J Tang, W Guo, J Shi, S Wang, H Gao, B Long arXiv preprint arXiv:2006.14827, 2020 | 25 | 2020 |
Multi-scale one-class recurrent neural networks for discrete event sequence anomaly detection Z Wang, Z Chen, J Ni, H Liu, H Chen, J Tang Proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data …, 2021 | 23 | 2021 |
Autodim: Field-aware embedding dimension searchin recommender systems X Zhao, H Liu, H Liu, J Tang, W Guo, J Shi, S Wang, H Gao, B Long Proceedings of the Web Conference 2021, 3015-3022, 2021 | 22 | 2021 |
Towards robust graph neural networks for noisy graphs with sparse labels E Dai, W Jin, H Liu, S Wang Proceedings of the Fifteenth ACM International Conference on Web Search and …, 2022 | 20 | 2022 |
Design and experimental evaluation of context-aware link-level adaptation J He, H Liu, P Cui, J Landon, O Altintas, R Vuyyuru, D Rajan, J Camp 2012 Proceedings IEEE INFOCOM, 2726-2730, 2012 | 14 | 2012 |
Usersim: User simulation via supervised generativeadversarial network X Zhao, L Xia, L Zou, H Liu, D Yin, J Tang Proceedings of the Web Conference 2021, 3582-3589, 2021 | 12 | 2021 |
A measurement study of white spaces across diverse population densities P Cui, H Liu, D Rajan, J Camp 2014 12th International Symposium on Modeling and Optimization in Mobile, Ad …, 2014 | 12 | 2014 |
Leveraging diverse propagation and context for multi-modal vehicular applications P Cui, H Liu, J He, O Altintas, R Vuyyuru, D Rajan, J Camp 2013 IEEE 5th International Symposium on Wireless Vehicular Communications …, 2013 | 11 | 2013 |
Yet meta learning can adapt fast, it can also break easily H Xu, Y Li, X Liu, H Liu, J Tang Proceedings of the 2021 SIAM International Conference on Data Mining (SDM …, 2021 | 9 | 2021 |
Learning multi-level dependencies for robust word recognition Z Wang, H Liu, J Tang, S Yang, GY Huang, Z Liu Proceedings of the AAAI Conference on Artificial Intelligence 34 (05), 9250-9257, 2020 | 9 | 2020 |