Seguir
Ruiming Tang
Título
Citado por
Citado por
Año
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
27442017
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
2212018
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
1822020
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
1572020
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
1552019
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
1472020
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
1472019
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
1412018
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
1362019
Deep learning for click-through rate estimation
W Zhang, J Qin, W Guo, R Tang, X He
arXiv preprint arXiv:2104.10584, 2021
902021
An embedding learning framework for numerical features in ctr prediction
H Guo, B Chen, R Tang, W Zhang, Z Li, X He
Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021
832021
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
822020
Graphsail: Graph structure aware incremental learning for recommender systems
Y Xu, Y Zhang, W Guo, H Guo, R Tang, M Coates
Proceedings of the 29th ACM International Conference on Information …, 2020
782020
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
752018
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
682019
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
622015
Dropnas: Grouped operation dropout for differentiable architecture search
W Hong, G Li, W Zhang, R Tang, Y Wang, Z Li, Y Yu
arXiv preprint arXiv:2201.11679, 2022
612022
Towards open-world recommendation with knowledge augmentation from large language models
Y Xi, W Liu, J Lin, J Zhu, B Chen, R Tang, W Zhang, R Zhang, Y Yu
arXiv preprint arXiv:2306.10933, 2023
592023
State representation modeling for deep reinforcement learning based recommendation
F Liu, R Tang, X Li, W Zhang, Y Ye, H Chen, H Guo, Y Zhang, X He
Knowledge-Based Systems 205, 106170, 2020
562020
Dual graph enhanced embedding neural network for CTR prediction
W Guo, R Su, R Tan, H Guo, Y Zhang, Z Liu, R Tang, X He
Proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data …, 2021
532021
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
Artículos 1–20