Quanyu Dai (戴全宇)
Quanyu Dai (戴全宇)
Huawei Noah's Ark Lab
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Cited by
Cited by
Adversarial network embedding
Q Dai, Q Li, J Tang, D Wang
Thirty-Second AAAI Conference on Artificial Intelligence, 2018
Adversarial Training Methods for Network Embedding
Q Dai, X Shen, L Zhang, Q Li, D Wang
The World Wide Web Conference, 329-339, 2019
Network Together: Node Classification via Cross-Network Deep Network Embedding
X Shen, Q Dai, S Mao, F Chung, KS Choi
IEEE Transactions on Neural Networks and Learning Systems, 2020
Adversarial Deep Network Embedding for Cross-Network Node Classification
X Shen, Q Dai, F Chung, W Lu, KS Choi
Proceedings of the AAAI Conference on Artificial Intelligence 34 (03), 2991-2999, 2020
Graph Transfer Learning via Adversarial Domain Adaptation with Graph Convolution
Q Dai, XM Wu, J Xiao, X Shen, D Wang
IEEE Transactions on Knowledge and Data Engineering, 2022
Top-N Recommendation with Counterfactual User Preference Simulation
M Yang, Q Dai, Z Dong, X Chen, X He, J Wang
Proceedings of the 30th ACM International Conference on Information …, 2021
An attention-based model for conversion rate prediction with delayed feedback via post-click calibration
Y Su, L Zhang, Q Dai, B Zhang, J Yan, D Wang, Y Bao, S Xu, Y He, W Yan
International Joint Conference on Artificial Intelligence-Pacific Rim …, 2020
SimpleX: A Simple and Strong Baseline for Collaborative Filtering
K Mao, J Zhu, J Wang, Q Dai, Z Dong, X Xiao, X He
Proceedings of the 30th ACM International Conference on Information …, 2021
Social Attentive Deep Q-networks for Recommender Systems
Y Lei, Z Wang, W Li, H Pei, Q Dai
IEEE Transactions on Knowledge and Data Engineering, 2020
Regularized Adversarial Sampling and Deep Time-aware Attention for Click-Through Rate Prediction
Y Wang, L Zhang, Q Dai, F Sun, B Zhang, Y He, W Yan, Y Bao
Proceedings of the 28th ACM International Conference on Information and …, 2019
Ranking network embedding via adversarial learning
Q Dai, Q Li, L Zhang, D Wang
23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD …, 2019
Metadata-driven Task Relation Discovery for Multi-task Learning.
Z Zheng, Y Wang, Q Dai, H Zheng, D Wang
IJCAI, 4426-4432, 2019
On the Opportunity of Causal Learning in Recommendation Systems: Foundation, Estimation, Prediction and Challenges
P Wu, H Li, Y Deng, W Hu, Q Dai, Z Dong, J Sun, R Zhang, XH Zhou
IJCAI, 2022
Dimensionwise Separable 2-D Graph Convolution for Unsupervised and Semi-Supervised Learning on Graphs
Q Li, X Zhang, H Liu, Q Dai, XM Wu
Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021
Contextual Anomaly Detection in Solder Paste Inspection with Multi-Task Learning
Z Zheng, J Pu, L Liu, D Wang, X Mei, S Zhang, Q Dai
ACM Transactions on Intelligent Systems and Technology (TIST) 11 (6), 1-17, 2020
Personalized knowledge-aware recommendation with collaborative and attentive graph convolutional networks
Q Dai, XM Wu, L Fan, Q Li, H Liu, X Zhang, D Wang, G Lin, K Yang
Pattern Recognition 128, 108628, 2022
Dual Sequence Transformer for Query-based Interactive Recommendation
G Cai, X Li, Q Dai, G Wang, Z Dong, C Zhang, X He, L Shang
2021 22nd IEEE International Conference on Mobile Data Management (MDM), 139-144, 2021
Adversarially Regularized Graph Attention Networks for Inductive Learning on Partially Labeled Graphs
J Xiao, Q Dai, X Xie, J Lam, KW Kwok
arXiv preprint arXiv:2106.03393, 2021
Adversarial Learning for Overlapping Community Detection and Network Embedding
J Chen, Z Gong, Q Dai, C Yuan, W Liu
ECAI 2020, 1071-1078, 2020
BARS: Towards Open Benchmarking for Recommender Systems
J Zhu, K Mao, Q Dai, L Su, R Ma, J Liu, G Cai, Z Dou, X Xiao, R Zhang
arXiv preprint arXiv:2205.09626, 2022
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