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2020 – today
- 2024
[j10]Jiaren Xiao
, Quanyu Dai, Xiao Shen, Xiaochen Xie, Jing Dai, James Lam, Ka-Wai Kwok:
Semi-supervised domain adaptation on graphs with contrastive learning and minimax entropy. Neurocomputing 580: 127469 (2024)- [c34]Lei Wang, Xu Chen, Zhenhua Dong, Quanyu Dai:
Would You Like Your Data to Be Trained? A User Controllable Recommendation Framework. AAAI 2024: 21673-21680 - [c33]Jingsen Zhang, Xiaohe Bo, Chenxi Wang, Quanyu Dai, Zhenhua Dong, Ruiming Tang, Xu Chen:
Active Explainable Recommendation with Limited Labeling Budgets. ICASSP 2024: 5375-5379 - [c32]Sunhao Dai, Ninglu Shao, Jieming Zhu, Xiao Zhang, Zhenhua Dong, Jun Xu, Quanyu Dai, Ji-Rong Wen:
Modeling User Attention in Music Recommendation. ICDE 2024: 761-774 - [c31]Qijiong Liu, Jieming Zhu, Yanting Yang, Quanyu Dai, Zhaocheng Du, Xiao-Ming Wu, Zhou Zhao, Rui Zhang, Zhenhua Dong:
Multimodal Pretraining, Adaptation, and Generation for Recommendation: A Survey. KDD 2024: 6566-6576 - [c30]Haojie Wei, Jun Yuan, Rui Zhang, Quanyu Dai, Yueguo Chen:
MAJL: A Model-Agnostic Joint Learning Framework for Music Source Separation and Pitch Estimation. ACM Multimedia 2024: 8623-8632 - [c29]Qijiong Liu, Jieming Zhu, Quanyu Dai, Xiao-Ming Wu:
Benchmarking News Recommendation in the Era of Green AI. WWW (Companion Volume) 2024: 971-974 - [i25]Qijiong Liu, Jieming Zhu, Quanyu Dai, Xiao-Ming Wu:
Benchmarking News Recommendation in the Era of Green AI. CoRR abs/2403.04736 (2024) - [i24]Qijiong Liu, Jieming Zhu, Yanting Yang, Quanyu Dai, Zhaocheng Du, Xiao-Ming Wu, Zhou Zhao, Rui Zhang, Zhenhua Dong:
Multimodal Pretraining, Adaptation, and Generation for Recommendation: A Survey. CoRR abs/2404.00621 (2024) - [i23]Zeyu Zhang, Xiaohe Bo, Chen Ma, Rui Li, Xu Chen, Quanyu Dai, Jieming Zhu, Zhenhua Dong, Ji-Rong Wen:
A Survey on the Memory Mechanism of Large Language Model based Agents. CoRR abs/2404.13501 (2024) - [i22]Zeyu Zhang, Quanyu Dai, Luyu Chen, Zeren Jiang, Rui Li, Jieming Zhu, Xu Chen, Yi Xie, Zhenhua Dong, Ji-Rong Wen:
MemSim: A Bayesian Simulator for Evaluating Memory of LLM-based Personal Assistants. CoRR abs/2409.20163 (2024) - 2023
- [j9]Jiaren Xiao, Quanyu Dai, Xiaochen Xie, James Lam, Ka-Wai Kwok:
Adversarially regularized graph attention networks for inductive learning on partially labeled graphs. Knowl. Based Syst. 268: 110456 (2023) - [j8]Quanyu Dai, Xiao-Ming Wu, Jiaren Xiao, Xiao Shen, Dan Wang:
Graph Transfer Learning via Adversarial Domain Adaptation With Graph Convolution. IEEE Trans. Knowl. Data Eng. 35(5): 4908-4922 (2023) - [j7]Jiaren Xiao, Quanyu Dai, Xiaochen Xie, Qi Dou, Ka-Wai Kwok, James Lam:
Domain Adaptive Graph Infomax via Conditional Adversarial Networks. IEEE Trans. Netw. Sci. Eng. 10(1): 35-52 (2023) - [c28]Haoxuan Li, Quanyu Dai, Yuru Li, Yan Lyu, Zhenhua Dong, Xiao-Hua Zhou, Peng Wu:
Multiple Robust Learning for Recommendation. AAAI 2023: 4417-4425 - [c27]Zhenlei Wang, Xu Chen, Rui Zhou, Quanyu Dai, Zhenhua Dong, Ji-Rong Wen:
Sequential Recommendation with User Causal Behavior Discovery. ICDE 2023: 28-40 - [c26]Qizhou Wang, Junjie Ye, Feng Liu, Quanyu Dai, Marcus Kalander, Tongliang Liu, Jianye Hao, Bo Han:
Out-of-distribution Detection with Implicit Outlier Transformation. ICLR 2023 - [c25]Xu Chen, Jingsen Zhang, Lei Wang, Quanyu Dai, Zhenhua Dong, Ruiming Tang, Rui Zhang, Li Chen, Xin Zhao, Ji-Rong Wen:
REASONER: An Explainable Recommendation Dataset with Comprehensive Labeling Ground Truths. NeurIPS 2023 - [c24]Hao Wang, Jiajun Fan, Zhichao Chen, Haoxuan Li, Weiming Liu, Tianqiao Liu, Quanyu Dai, Yichao Wang, Zhenhua Dong, Ruiming Tang:
Optimal Transport for Treatment Effect Estimation. NeurIPS 2023 - [c23]Jieming Zhu, Qinglin Jia, Guohao Cai, Quanyu Dai, Jingjie Li, Zhenhua Dong, Ruiming Tang, Rui Zhang:
FINAL: Factorized Interaction Layer for CTR Prediction. SIGIR 2023: 2006-2010 - [c22]Zhiheng Zhang, Quanyu Dai, Xu Chen, Zhenhua Dong, Ruiming Tang:
Robust Causal Inference for Recommender System to Overcome Noisy Confounders. SIGIR 2023: 2349-2353 - [c21]Xiaofan Liu, Qinglin Jia, Chuhan Wu, Jingjie Li, Quanyu Dai, Lin Bo, Rui Zhang, Ruiming Tang:
Task Adaptive Multi-learner Network for Joint CTR and CVR Estimation. WWW (Companion Volume) 2023: 490-494 - [c20]Jingsen Zhang, Xu Chen, Jiakai Tang, Weiqi Shao, Quanyu Dai, Zhenhua Dong, Rui Zhang:
Recommendation with Causality enhanced Natural Language Explanations. WWW 2023: 876-886 - [i21]Xu Chen, Jingsen Zhang, Lei Wang, Quanyu Dai, Zhenhua Dong, Ruiming Tang, Rui Zhang, Li Chen, Ji-Rong Wen:
REASONER: An Explainable Recommendation Dataset with Multi-aspect Real User Labeled Ground Truths Towards more Measurable Explainable Recommendation. CoRR abs/2303.00168 (2023) - [i20]Qizhou Wang, Junjie Ye, Feng Liu, Quanyu Dai, Marcus Kalander, Tongliang Liu, Jianye Hao, Bo Han:
Out-of-distribution Detection with Implicit Outlier Transformation. CoRR abs/2303.05033 (2023) - [i19]Qijiong Liu, Jieming Zhu, Quanyu Dai, Xiao-Ming Wu:
Only Encode Once: Making Content-based News Recommender Greener. CoRR abs/2308.14155 (2023) - [i18]Jiaren Xiao, Quanyu Dai, Xiao Shen, Xiaochen Xie, Jing Dai, James Lam, Ka-Wai Kwok:
Semi-supervised Domain Adaptation on Graphs with Contrastive Learning and Minimax Entropy. CoRR abs/2309.07402 (2023) - [i17]Hao Wang, Zhichao Chen, Jiajun Fan, Haoxuan Li, Tianqiao Liu, Weiming Liu, Quanyu Dai, Yichao Wang, Zhenhua Dong, Ruiming Tang:
Optimal Transport for Treatment Effect Estimation. CoRR abs/2310.18286 (2023) - 2022
- [j6]Quanyu Dai, Zhenhua Dong, Xu Chen:
Debiased recommendation with neural stratification. AI Open 3: 213-217 (2022) - [j5]Quanyu Dai, Xiao-Ming Wu, Lu Fan, Qimai Li, Han Liu, Xiaotong Zhang, Dan Wang, Guli Lin, Keping Yang:
Personalized knowledge-aware recommendation with collaborative and attentive graph convolutional networks. Pattern Recognit. 128: 108628 (2022) - [j4]Yu Lei, Zhitao Wang, Wenjie Li, Hongbin Pei, Quanyu Dai:
Social Attentive Deep Q-Networks for Recommender Systems. IEEE Trans. Knowl. Data Eng. 34(5): 2443-2457 (2022) - [c19]Quanyu Dai, Yalei Lv, Jieming Zhu, Junjie Ye, Zhenhua Dong, Rui Zhang, Shu-Tao Xia, Ruiming Tang:
LCD: Adaptive Label Correction for Denoising Music Recommendation. CIKM 2022: 3903-3907 - [c18]Qijiong Liu, Jieming Zhu, Quanyu Dai, Xiaoming Wu:
Boosting Deep CTR Prediction with a Plug-and-Play Pre-trainer for News Recommendation. COLING 2022: 2823-2833 - [c17]Peng Wu, Haoxuan Li, Yuhao Deng, Wenjie Hu, Quanyu Dai, Zhenhua Dong, Jie Sun, Rui Zhang, Xiao-Hua Zhou:
On the Opportunity of Causal Learning in Recommendation Systems: Foundation, Estimation, Prediction and Challenges. IJCAI 2022: 5646-5653 - [c16]Quanyu Dai, Haoxuan Li, Peng Wu, Zhenhua Dong, Xiao-Hua Zhou, Rui Zhang, Rui Zhang, Jie Sun:
A Generalized Doubly Robust Learning Framework for Debiasing Post-Click Conversion Rate Prediction. KDD 2022: 252-262 - [c15]Xiao Zhang, Sunhao Dai, Jun Xu, Zhenhua Dong, Quanyu Dai, Ji-Rong Wen:
Counteracting User Attention Bias in Music Streaming Recommendation via Reward Modification. KDD 2022: 2504-2514 - [c14]Guohao Cai, Jieming Zhu, Quanyu Dai, Zhenhua Dong, Xiuqiang He, Ruiming Tang, Rui Zhang:
ReLoop: A Self-Correction Continual Learning Loop for Recommender Systems. SIGIR 2022: 2692-2697 - [c13]Jieming Zhu, Quanyu Dai, Liangcai Su, Rong Ma, Jinyang Liu, Guohao Cai, Xi Xiao, Rui Zhang:
BARS: Towards Open Benchmarking for Recommender Systems. SIGIR 2022: 2912-2923 - [i16]Peng Wu, Haoxuan Li, Yuhao Deng, Wenjie Hu, Quanyu Dai, Zhenhua Dong, Jie Sun, Rui Zhang, Xiao-Hua Zhou:
Causal Analysis Framework for Recommendation. CoRR abs/2201.06716 (2022) - [i15]Yan Lyu, Sunhao Dai, Peng Wu, Quanyu Dai, Yuhao Deng, Wenjie Hu, Zhenhua Dong, Jun Xu, Shengyu Zhu, Xiao-Hua Zhou:
A Semi-Synthetic Dataset Generation Framework for Causal Inference in Recommender Systems. CoRR abs/2202.11351 (2022) - [i14]Zhenlei Wang, Xu Chen, Zhenhua Dong, Quanyu Dai, Ji-Rong Wen:
Sequential Recommendation with Causal Behavior Discovery. CoRR abs/2204.00216 (2022) - [i13]Guohao Cai, Jieming Zhu, Quanyu Dai, Zhenhua Dong, Xiuqiang He, Ruiming Tang, Rui Zhang:
ReLoop: A Self-Correction Continual Learning Loop for Recommender Systems. CoRR abs/2204.11165 (2022) - [i12]Jieming Zhu, Quanyu Dai, Liangcai Su, Rong Ma, Jinyang Liu, Guohao Cai, Xi Xiao, Rui Zhang:
BARS: Towards Open Benchmarking for Recommender Systems. CoRR abs/2205.09626 (2022) - [i11]Quanyu Dai, Zhenhua Dong, Xu Chen:
Debiased Recommendation with Neural Stratification. CoRR abs/2208.07281 (2022) - [i10]Lei Wang, Xu Chen, Quanyu Dai, Zhenhua Dong:
Recommendation with User Active Disclosing Willingness. CoRR abs/2211.01155 (2022) - [i9]Quanyu Dai, Haoxuan Li, Peng Wu, Zhenhua Dong, Xiao-Hua Zhou, Rui Zhang, Rui Zhang, Jie Sun:
A Generalized Doubly Robust Learning Framework for Debiasing Post-Click Conversion Rate Prediction. CoRR abs/2211.06684 (2022) - 2021
- [j3]Quanyu Dai, Xiao Shen, Zimu Zheng, Liang Zhang, Qiang Li, Dan Wang:
Adversarial training regularization for negative sampling based network embedding. Inf. Sci. 579: 199-217 (2021) - [j2]Xiao Shen, Quanyu Dai, Sitong Mao, Fu-Lai Chung, Kup-Sze Choi:
Network Together: Node Classification via Cross-Network Deep Network Embedding. IEEE Trans. Neural Networks Learn. Syst. 32(5): 1935-1948 (2021) - [c12]Kelong Mao, Jieming Zhu, Jinpeng Wang, Quanyu Dai, Zhenhua Dong, Xi Xiao, Xiuqiang He:
SimpleX: A Simple and Strong Baseline for Collaborative Filtering. CIKM 2021: 1243-1252 - [c11]Mengyue Yang, Quanyu Dai, Zhenhua Dong, Xu Chen, Xiuqiang He, Jun Wang:
Top-N Recommendation with Counterfactual User Preference Simulation. CIKM 2021: 2342-2351 - [c10]Qimai Li, Xiaotong Zhang, Han Liu, Quanyu Dai, Xiao-Ming Wu:
Dimensionwise Separable 2-D Graph Convolution for Unsupervised and Semi-Supervised Learning on Graphs. KDD 2021: 953-963 - [c9]Guohao Cai, Xiaoguang Li, Quanyu Dai, Gang Wang, Zhenhua Dong, Chaoliang Zhang, Xiuqiang He, Lifeng Shang:
Dual Sequence Transformer for Query-based Interactive Recommendation. MDM 2021: 139-144 - [i8]Jiaren Xiao, Quanyu Dai, Xiaochen Xie, James Lam, Ka-Wai Kwok:
Adversarially Regularized Graph Attention Networks for Inductive Learning on Partially Labeled Graphs. CoRR abs/2106.03393 (2021) - [i7]Mengyue Yang, Quanyu Dai, Zhenhua Dong, Xu Chen, Xiuqiang He, Jun Wang:
Top-N Recommendation with Counterfactual User Preference Simulation. CoRR abs/2109.02444 (2021) - [i6]Kelong Mao, Jieming Zhu, Jinpeng Wang, Quanyu Dai, Zhenhua Dong, Xi Xiao, Xiuqiang He:
SimpleX: A Simple and Strong Baseline for Collaborative Filtering. CoRR abs/2109.12613 (2021) - 2020
- [j1]Zimu Zheng, Jie Pu, Linghui Liu, Dan Wang, Xiangming Mei, Sen Zhang, Quanyu Dai:
Contextual Anomaly Detection in Solder Paste Inspection with Multi-Task Learning. ACM Trans. Intell. Syst. Technol. 11(6): 65:1-65:17 (2020) - [c8]Xiao Shen, Quanyu Dai, Fu-Lai Chung, Wei Lu, Kup-Sze Choi:
Adversarial Deep Network Embedding for Cross-Network Node Classification. AAAI 2020: 2991-2999 - [c7]Junyang Chen, Zhiguo Gong, Quanyu Dai, Chunyuan Yuan, Weiwen Liu:
Adversarial Learning for Overlapping Community Detection and Network Embedding. ECAI 2020: 1071-1078 - [c6]Yumin Su, Liang Zhang, Quanyu Dai, Bo Zhang, Jinyao Yan, Dan Wang, Yongjun Bao, Sulong Xu, Yang He, Weipeng Yan:
An Attention-based Model for Conversion Rate Prediction with Delayed Feedback via Post-click Calibration. IJCAI 2020: 3522-3528 - [i5]Xiao Shen, Quanyu Dai, Fu-Lai Chung, Wei Lu, Kup-Sze Choi:
Adversarial Deep Network Embedding for Cross-network Node Classification. CoRR abs/2002.07366 (2020)
2010 – 2019
- 2019
- [c5]Yikai Wang, Liang Zhang, Quanyu Dai, Fuchun Sun, Bo Zhang, Yang He, Weipeng Yan, Yongjun Bao:
Regularized Adversarial Sampling and Deep Time-aware Attention for Click-Through Rate Prediction. CIKM 2019: 349-358 - [c4]Zimu Zheng, Yuqi Wang, Quanyu Dai, Huadi Zheng, Dan Wang:
Metadata-driven Task Relation Discovery for Multi-task Learning. IJCAI 2019: 4426-4432 - [c3]Quanyu Dai, Qiang Li, Liang Zhang, Dan Wang:
Ranking Network Embedding via Adversarial Learning. PAKDD (3) 2019: 27-39 - [c2]Quanyu Dai, Xiao Shen, Liang Zhang, Qiang Li, Dan Wang:
Adversarial Training Methods for Network Embedding. WWW 2019: 329-339 - [i4]Quanyu Dai, Xiao Shen, Liang Zhang, Qiang Li, Dan Wang:
Adversarial Training Methods for Network Embedding. CoRR abs/1908.11514 (2019) - [i3]Quanyu Dai, Xiao Shen, Xiao-Ming Wu, Dan Wang:
Network Transfer Learning via Adversarial Domain Adaptation with Graph Convolution. CoRR abs/1909.01541 (2019) - [i2]Yikai Wang, Liang Zhang, Quanyu Dai, Fuchun Sun, Bo Zhang, Yang He, Weipeng Yan, Yongjun Bao:
Regularized Adversarial Sampling and Deep Time-aware Attention for Click-Through Rate Prediction. CoRR abs/1911.00886 (2019) - 2018
- [c1]Quanyu Dai, Qiang Li, Jian Tang, Dan Wang:
Adversarial Network Embedding. AAAI 2018: 2167-2174 - 2017
- [i1]Quanyu Dai, Qiang Li, Jian Tang, Dan Wang:
Adversarial Network Embedding. CoRR abs/1711.07838 (2017)
Coauthor Index
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last updated on 2024-11-13 23:50 CET by the dblp team
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