Ruiming Tang
Ruiming Tang
Потвърден имейл адрес: huawei.com
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Позовавания
Позовавания
Година
DeepFM: a factorization-machine based neural network for CTR prediction
H Guo, R Tang, Y Ye, Z Li, X He
arXiv preprint arXiv:1703.04247, 2017
11002017
Product-based neural networks for user response prediction over multi-field categorical data
Y Qu, B Fang, W Zhang, R Tang, M Niu, H Guo, Y Yu, X He
ACM Transactions on Information Systems (TOIS) 37 (1), 1-35, 2018
1092018
Feature generation by convolutional neural network for click-through rate prediction
B Liu, R Tang, Y Chen, J Yu, H Guo, Y Zhang
The World Wide Web Conference, 1119-1129, 2019
682019
Large-scale interactive recommendation with tree-structured policy gradient
H Chen, X Dai, H Cai, W Zhang, X Wang, R Tang, Y Zhang, Y Yu
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 3312-3320, 2019
662019
Autofis: Automatic feature interaction selection in factorization models for click-through rate prediction
B Liu, C Zhu, G Li, W Zhang, J Lai, R Tang, X He, Z Li, Y Yu
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020
622020
Deep reinforcement learning based recommendation with explicit user-item interactions modeling
F Liu, R Tang, X Li, W Zhang, Y Ye, H Chen, H Guo, Y Zhang
arXiv preprint arXiv:1810.12027, 2018
582018
An efficient and truthful pricing mechanism for team formation in crowdsourcing markets
Q Liu, T Luo, R Tang, S Bressan
2015 IEEE International Conference on Communications (ICC), 567-572, 2015
432015
Deepfm: An end-to-end wide & deep learning framework for CTR prediction
H Guo, R Tang, Y Ye, Z Li, X He, Z Dong
arXiv preprint arXiv:1804.04950, 2018
352018
Interactive recommender system via knowledge graph-enhanced reinforcement learning
S Zhou, X Dai, H Chen, W Zhang, K Ren, R Tang, X He, Y Yu
Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020
332020
Multi-graph convolution collaborative filtering
J Sun, Y Zhang, C Ma, M Coates, H Guo, R Tang, X He
2019 IEEE International Conference on Data Mining (ICDM), 1306-1311, 2019
322019
Dropnas: Grouped operation dropout for differentiable architecture search
W Hong, G Li, W Zhang, R Tang, Y Wang, Z Li, Y Yu
Proceedings of the Twenty-Ninth International Conference on International …, 2021
262021
The price is right
R Tang, H Wu, Z Bao, S Bressan, P Valduriez
International Conference on Database and Expert Systems Applications, 380-394, 2013
222013
Neighbor interaction aware graph convolution networks for recommendation
J Sun, Y Zhang, W Guo, H Guo, R Tang, X He, C Ma, M Coates
Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020
212020
PAL: a position-bias aware learning framework for CTR prediction in live recommender systems
H Guo, J Yu, Q Liu, R Tang, Y Zhang
Proceedings of the 13th ACM Conference on Recommender Systems, 452-456, 2019
202019
A framework for recommending accurate and diverse items using bayesian graph convolutional neural networks
J Sun, W Guo, D Zhang, Y Zhang, F Regol, Y Hu, H Guo, R Tang, H Yuan, ...
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020
192020
AutoFeature: Searching for Feature Interactions and Their Architectures for Click-through Rate Prediction
F Khawar, X Hang, R Tang, B Liu, Z Li, X He
Proceedings of the 29th ACM International Conference on Information …, 2020
172020
AutoGroup: Automatic feature grouping for modelling explicit high-order feature interactions in CTR prediction
B Liu, N Xue, H Guo, R Tang, S Zafeiriou, X He, Z Li
Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020
172020
End-to-end deep reinforcement learning based recommendation with supervised embedding
F Liu, H Guo, X Li, R Tang, Y Ye, X He
Proceedings of the 13th International Conference on Web Search and Data …, 2020
162020
Field-aware probabilistic embedding neural network for ctr prediction
W Liu, R Tang, J Li, J Yu, H Guo, X He, S Zhang
Proceedings of the 12th ACM Conference on Recommender Systems, 412-416, 2018
162018
A framework for conditioning uncertain relational data
R Tang, R Cheng, H Wu, S Bressan
International Conference on Database and Expert Systems Applications, 71-87, 2012
162012
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