Qingyun Wu
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Estimation-action-reflection: Towards deep interaction between conversational and recommender systems
W Lei, X He, Y Miao, Q Wu, R Hong, MY Kan, TS Chua
Proceedings of the 13th International Conference on Web Search and Data …, 2020
Contextual Bandits in a Collaborative Environment
Q Wu, H Wang, Q Gu, H Wang
The 39th International ACM SIGIR conference on Research and Development in …, 2016
Factorization bandits for interactive recommendation
H Wang, Q Wu, H Wang
Thirty-First AAAI Conference on Artificial Intelligence, 2017
Learning Hidden Features for Contextual Bandits
H Wang, Q Wu, H Wang
CIKM '16, 1633-1642, 2016
Learning contextual bandits in a non-stationary environment
Q Wu, N Iyer, H Wang
The 41st International ACM SIGIR Conference on Research & Development in …, 2018
Returning is believing: Optimizing long-term user engagement in recommender systems
Q Wu, H Wang, L Hong, Y Shi
Proceedings of the 2017 ACM on Conference on Information and Knowledge …, 2017
Seamlessly unifying attributes and items: Conversational recommendation for cold-start users
S Li, W Lei, Q Wu, X He, P Jiang, TS Chua
ACM Transactions on Information Systems (TOIS) 39 (4), 1-29, 2021
Fast distributed bandits for online recommendation systems
K Mahadik, Q Wu, S Li, A Sabne
Proceedings of the 34th ACM international conference on supercomputing, 1-13, 2020
Factorization bandits for online influence maximization
Q Wu, Z Li, H Wang, W Chen, H Wang
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019
Bandit learning with implicit feedback
Y Qi, Q Wu, H Wang, J Tang, M Sun
Advances in Neural Information Processing Systems 31, 2018
Variance reduction in gradient exploration for online learning to rank
H Wang, S Kim, E McCord-Snook, Q Wu, H Wang
Proceedings of the 42nd International ACM SIGIR Conference on Research and …, 2019
Dynamic ensemble of contextual bandits to satisfy users' changing interests
Q Wu, H Wang, Y Li, H Wang
The World Wide Web Conference, 2080-2090, 2019
Flo: Fast and lightweight hyperparameter optimization for automl
C Wang, Q Wu
arXiv e-prints, arXiv: 1911.04706, 2019
Global and Local Differential Privacy for Collaborative Bandits
H Wang, Q Zhao, Q Wu, S Chopra, A Khaitan, H Wang
Fourteenth ACM Conference on Recommender Systems, 150-159, 2020
Frugal optimization for cost-related hyperparameters
Q Wu, C Wang, S Huang
Proceedings of the AAAI Conference on Artificial Intelligence 35 (12), 10347 …, 2021
Unifying Clustered and Non-stationary Bandits
C Li, Q Wu, H Wang
International Conference on Artificial Intelligence and Statistics, 1063-1071, 2021
Economic hyperparameter optimization with blended search strategy
C Wang, Q Wu, S Huang, A Saied
International Conference on Learning Representations, 2020
ChaCha for Online AutoML
Q Wu, C Wang, J Langford, P Mineiro, M Rossi
arXiv preprint arXiv:2106.04815, 2021
Learning by Exploration: New Challenges in Real-World Environments
Q Wu, H Wang, H Wang
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020
Fair AutoML
Q Wu, C Wang
arXiv preprint arXiv:2111.06495, 2021
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