Author:
Xia Yu,Xie Zhihui,Yu Tong,Zhao Canzhe,Li Shuai
Publisher
Springer Science and Business Media LLC
Reference61 articles.
1. Agrawal, S., Jia, R.: Optimistic posterior sampling for reinforcement learning: Worst-case regret bounds. In: Proceedings of the 31st International Conference on Neural Information Processing Systems, pp. 1184–1194. Curran Associates Inc., Red Hook, NIPS’17 (2017)
2. Aliannejadi, M., Zamani, H., Crestani, F., et al.: Asking clarifying questions in open-domain information-seeking conversations. In: Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval. Association for Computing Machinery, New York, SIGIR’19, pp. 475–484 (2019) https://doi.org/10.1145/3331184.3331265
3. Chapelle, O., Joachims, T., Radlinski, F., et al.: Large-scale validation and analysis of interleaved search evaluation. ACM Trans. Inf. Syst. 30(1), 1–41 (2012)
4. Chen, Q., Lin, J., Zhang, Y., et al.: Towards knowledge-based recommender dialog system. In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp. 1803–1813, https://doi.org/10.18653/v1/D19-1189, https://www.aclweb.org/anthology/D19-1189 (2019)
5. Chin, W.S., Yuan, B.W., Yang, M.Y., et al.: Libmf: a library for parallel matrix factorization in shared-memory systems. J. Mach. Learn. Res. 17(86), 1–5 (2016)