| Deep reinforcement learning for dynamic multichannel access in wireless networks S Wang, H Liu, PH Gomes, B Krishnamachari IEEE Transactions on Cognitive Communications and Networking 4 (2), 257-265, 2018 | 465 | 2018 |
| Neural interaction transparency (nit): Disentangling learned interactions for improved interpretability M Tsang, H Liu, S Purushotham, P Murali, Y Liu Advances in Neural Information Processing Systems 31, 5804-5813, 2018 | 74 | 2018 |
| CoSTCo: A neural tensor completion model for sparse tensors H Liu, Y Li, M Tsang, Y Liu Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 71 | 2019 |
| Feature interaction interpretability: A case for explaining ad-recommendation systems via neural interaction detection M Tsang, D Cheng, H Liu, X Feng, E Zhou, Y Liu International Conference on Learning Representations (ICLR), 2020 | 63 | 2020 |
| Reinforcement mechanism design: With applications to dynamic pricing in sponsored search auctions W Shen, B Peng, H Liu, M Zhang, R Qian, Y Hong, Z Guo, Z Ding, P Lu, ... Proceedings of the AAAI Conference on Artificial Intelligence 34 (02), 2236-2243, 2020 | 61 | 2020 |
| Deep reinforcement learning for dynamic multichannel access S Wang, H Liu, PH Gomes, B Krishnamachari International Conference on Computing, Networking and Communications (ICNC …, 2017 | 42 | 2017 |
