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Yongchun Zhu
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2020 – today
- 2024
- [j10]Yiqing Wu, Ruobing Xie, Yongchun Zhu, Fuzhen Zhuang, Xu Zhang, Leyu Lin, Qing He:
Personalized Prompt for Sequential Recommendation. IEEE Trans. Knowl. Data Eng. 36(7): 3376-3389 (2024) - [j9]Yuting Zhang, Ying Sun, Fuzhen Zhuang, Yongchun Zhu, Zhulin An, Yongjun Xu:
Triple Dual Learning for Opinion-based Explainable Recommendation. ACM Trans. Inf. Syst. 42(3): 70:1-70:27 (2024) - [c28]Guanyu Jiang, Fuzhen Zhuang, Bowen Song, Yongchun Zhu, Ying Sun, Weiqiang Wang, Deqing Wang:
SeqSHAP: Subsequence Level Shapley Value Explanations for Sequential Predictions. DASFAA (4) 2024: 89-104 - [c27]Yuting Zhang, Yiqing Wu, Ruidong Han, Ying Sun, Yongchun Zhu, Xiang Li, Wei Lin, Fuzhen Zhuang, Zhulin An, Yongjun Xu:
Unified Dual-Intent Translation for Joint Modeling of Search and Recommendation. KDD 2024: 6291-6300 - [c26]Yongchun Zhu, Jingwu Chen, Ling Chen, Yitan Li, Feng Zhang, Zuotao Liu:
Interest Clock: Time Perception in Real-Time Streaming Recommendation System. SIGIR 2024: 2915-2919 - [i33]Yongchun Zhu, Jingwu Chen, Ling Chen, Yitan Li, Feng Zhang, Zuotao Liu:
Interest Clock: Time Perception in Real-Time Streaming Recommendation System. CoRR abs/2404.19357 (2024) - [i32]Yuting Zhang, Yiqing Wu, Ruidong Han, Ying Sun, Yongchun Zhu, Xiang Li, Wei Lin, Fuzhen Zhuang, Zhulin An, Yongjun Xu:
Unified Dual-Intent Translation for Joint Modeling of Search and Recommendation. CoRR abs/2407.00912 (2024) - 2023
- [j8]Yongchun Zhu, Fuzhen Zhuang, Xiangliang Zhang, Zhiyuan Qi, Zhi-Ping Shi, Juan Cao, Qing He:
Combat data shift in few-shot learning with knowledge graph. Frontiers Comput. Sci. 17(1): 171305 (2023) - [j7]Mengqi Zhan, Yang Li, Yongchun Zhu, Guangxi Yu, Yan Zhang, Bo Li, Weiping Wang:
Website-Aware Protocol Confusion Network for Emergent HTTP/3 Website Fingerprinting. IEEE Trans. Inf. Forensics Secur. 18: 2427-2439 (2023) - [j6]Yongchun Zhu, Qiang Sheng, Juan Cao, Qiong Nan, Kai Shu, Minghui Wu, Jindong Wang, Fuzhen Zhuang:
Memory-Guided Multi-View Multi-Domain Fake News Detection. IEEE Trans. Knowl. Data Eng. 35(7): 7178-7191 (2023) - [c25]Beizhe Hu, Qiang Sheng, Juan Cao, Yongchun Zhu, Danding Wang, Zhengjia Wang, Zhiwei Jin:
Learn over Past, Evolve for Future: Forecasting Temporal Trends for Fake News Detection. ACL (industry) 2023: 116-125 - [c24]Xin Qin, Jindong Wang, Shuo Ma, Wang Lu, Yongchun Zhu, Xing Xie, Yiqiang Chen:
Generalizable Low-Resource Activity Recognition with Diverse and Discriminative Representation Learning. KDD 2023: 1943-1953 - [c23]Yuting Zhang, Yiqing Wu, Ran Le, Yongchun Zhu, Fuzhen Zhuang, Ruidong Han, Xiang Li, Wei Lin, Zhulin An, Yongjun Xu:
Modeling Dual Period-Varying Preferences for Takeaway Recommendation. KDD 2023: 5628-5638 - [c22]Yiqing Wu, Ruobing Xie, Zhao Zhang, Yongchun Zhu, Fuzhen Zhuang, Jie Zhou, Yongjun Xu, Qing He:
Attacking Pre-trained Recommendation. SIGIR 2023: 1811-1815 - [c21]Yuxin Ying, Fuzhen Zhuang, Yongchun Zhu, Deqing Wang, Hongwei Zheng:
CAMUS: Attribute-Aware Counterfactual Augmentation for Minority Users in Recommendation. WWW 2023: 1396-1404 - [i31]Yiqing Wu, Ruobing Xie, Zhao Zhang, Yongchun Zhu, Fuzhen Zhuang, Jie Zhou, Yongjun Xu, Qing He:
Attacking Pre-trained Recommendation. CoRR abs/2305.03995 (2023) - [i30]Yuting Zhang, Yiqing Wu, Ran Le, Yongchun Zhu, Fuzhen Zhuang, Ruidong Han, Xiang Li, Wei Lin, Zhulin An, Yongjun Xu:
Modeling Dual Period-Varying Preferences for Takeaway Recommendation. CoRR abs/2306.04370 (2023) - [i29]Xin Qin, Jindong Wang, Shuo Ma, Wang Lu, Yongchun Zhu, Xing Xie, Yiqiang Chen:
Generalizable Low-Resource Activity Recognition with Diverse and Discriminative Representation Learning. CoRR abs/2306.04641 (2023) - [i28]Beizhe Hu, Qiang Sheng, Juan Cao, Yongchun Zhu, Danding Wang, Zhengjia Wang, Zhiwei Jin:
Learn over Past, Evolve for Future: Forecasting Temporal Trends for Fake News Detection. CoRR abs/2306.14728 (2023) - [i27]Qiong Nan, Qiang Sheng, Juan Cao, Yongchun Zhu, Danding Wang, Guang Yang, Jintao Li, Kai Shu:
Exploiting User Comments for Early Detection of Fake News Prior to Users' Commenting. CoRR abs/2310.10429 (2023) - 2022
- [j5]Shuokai Li, Ruobing Xie, Yongchun Zhu, Fuzhen Zhuang, Zhenwei Tang, Wayne Xin Zhao, Qing He:
Self-Supervised learning for Conversational Recommendation. Inf. Process. Manag. 59(6): 103067 (2022) - [c20]Qiang Sheng, Juan Cao, Xueyao Zhang, Rundong Li, Danding Wang, Yongchun Zhu:
Zoom Out and Observe: News Environment Perception for Fake News Detection. ACL (1) 2022: 4543-4556 - [c19]Qiong Nan, Danding Wang, Yongchun Zhu, Qiang Sheng, Yuhui Shi, Juan Cao, Jintao Li:
Improving Fake News Detection of Influential Domain via Domain- and Instance-Level Transfer. COLING 2022: 2834-2848 - [c18]Yiqing Wu, Ruobing Xie, Yongchun Zhu, Xiang Ao, Xin Chen, Xu Zhang, Fuzhen Zhuang, Leyu Lin, Qing He:
Multi-view Multi-behavior Contrastive Learning in Recommendation. DASFAA (2) 2022: 166-182 - [c17]Zhenwei Tang, Shichao Pei, Zhao Zhang, Yongchun Zhu, Fuzhen Zhuang, Robert Hoehndorf, Xiangliang Zhang:
Positive-Unlabeled Learning with Adversarial Data Augmentation for Knowledge Graph Completion. IJCAI 2022: 2248-2254 - [c16]Shuokai Li, Yongchun Zhu, Ruobing Xie, Zhenwei Tang, Zhao Zhang, Fuzhen Zhuang, Qing He, Hui Xiong:
Customized Conversational Recommender Systems. ECML/PKDD (2) 2022: 740-756 - [c15]Shuokai Li, Ruobing Xie, Yongchun Zhu, Xiang Ao, Fuzhen Zhuang, Qing He:
User-Centric Conversational Recommendation with Multi-Aspect User Modeling. SIGIR 2022: 223-233 - [c14]Yongchun Zhu, Qiang Sheng, Juan Cao, Shuokai Li, Danding Wang, Fuzhen Zhuang:
Generalizing to the Future: Mitigating Entity Bias in Fake News Detection. SIGIR 2022: 2120-2125 - [c13]Yiqing Wu, Ruobing Xie, Yongchun Zhu, Fuzhen Zhuang, Xiang Ao, Xu Zhang, Leyu Lin, Qing He:
Selective Fairness in Recommendation via Prompts. SIGIR 2022: 2657-2662 - [c12]Yongchun Zhu, Zhenwei Tang, Yudan Liu, Fuzhen Zhuang, Ruobing Xie, Xu Zhang, Leyu Lin, Qing He:
Personalized Transfer of User Preferences for Cross-domain Recommendation. WSDM 2022: 1507-1515 - [i26]Qiong Nan, Juan Cao, Yongchun Zhu, Yanyan Wang, Jintao Li:
MDFEND: Multi-domain Fake News Detection. CoRR abs/2201.00987 (2022) - [i25]Yongchun Zhu, Fuzhen Zhuang, Jindong Wang, Jingwu Chen, Zhi-Ping Shi, Wenjuan Wu, Qing He:
Multi-Representation Adaptation Network for Cross-domain Image Classification. CoRR abs/2201.01002 (2022) - [i24]Yongchun Zhu, Fuzhen Zhuang, Deqing Wang:
Aligning Domain-specific Distribution and Classifier for Cross-domain Classification from Multiple Sources. CoRR abs/2201.01003 (2022) - [i23]Yongchun Zhu, Dongbo Xi, Bowen Song, Fuzhen Zhuang, Shuai Chen, Xi Gu, Qing He:
Modeling Users' Behavior Sequences with Hierarchical Explainable Network for Cross-domain Fraud Detection. CoRR abs/2201.01004 (2022) - [i22]Yiqing Wu, Ruobing Xie, Yongchun Zhu, Xiang Ao, Xin Chen, Xu Zhang, Fuzhen Zhuang, Leyu Lin, Qing He:
Multi-view Multi-behavior Contrastive Learning in Recommendation. CoRR abs/2203.10576 (2022) - [i21]Qiang Sheng, Juan Cao, Xueyao Zhang, Rundong Li, Danding Wang, Yongchun Zhu:
Zoom Out and Observe: News Environment Perception for Fake News Detection. CoRR abs/2203.10885 (2022) - [i20]Shuokai Li, Ruobing Xie, Yongchun Zhu, Xiang Ao, Fuzhen Zhuang, Qing He:
User-Centric Conversational Recommendation with Multi-Aspect User Modeling. CoRR abs/2204.09263 (2022) - [i19]Yongchun Zhu, Qiang Sheng, Juan Cao, Shuokai Li, Danding Wang, Fuzhen Zhuang:
Generalizing to the Future: Mitigating Entity Bias in Fake News Detection. CoRR abs/2204.09484 (2022) - [i18]Zhenwei Tang, Shichao Pei, Zhao Zhang, Yongchun Zhu, Fuzhen Zhuang, Robert Hoehndorf, Xiangliang Zhang:
Positive-Unlabeled Learning with Adversarial Data Augmentation for Knowledge Graph Completion. CoRR abs/2205.00904 (2022) - [i17]Yiqing Wu, Ruobing Xie, Yongchun Zhu, Fuzhen Zhuang, Xiang Ao, Xu Zhang, Leyu Lin, Qing He:
Selective Fairness in Recommendation via Prompts. CoRR abs/2205.04682 (2022) - [i16]Yiqing Wu, Ruobing Xie, Yongchun Zhu, Fuzhen Zhuang, Xu Zhang, Leyu Lin, Qing He:
Personalized Prompts for Sequential Recommendation. CoRR abs/2205.09666 (2022) - [i15]Yongchun Zhu, Qiang Sheng, Juan Cao, Qiong Nan, Kai Shu, Minghui Wu, Jindong Wang, Fuzhen Zhuang:
Memory-Guided Multi-View Multi-Domain Fake News Detection. CoRR abs/2206.12808 (2022) - [i14]Shuokai Li, Yongchun Zhu, Ruobing Xie, Zhenwei Tang, Zhao Zhang, Fuzhen Zhuang, Qing He, Hui Xiong:
Customized Conversational Recommender Systems. CoRR abs/2207.00814 (2022) - [i13]Qiong Nan, Danding Wang, Yongchun Zhu, Qiang Sheng, Yuhui Shi, Juan Cao, Jintao Li:
Improving Fake News Detection of Influential Domain via Domain- and Instance-Level Transfer. CoRR abs/2209.08902 (2022) - 2021
- [j4]Fuzhen Zhuang, Zhiyuan Qi, Keyu Duan, Dongbo Xi, Yongchun Zhu, Hengshu Zhu, Hui Xiong, Qing He:
A Comprehensive Survey on Transfer Learning. Proc. IEEE 109(1): 43-76 (2021) - [j3]Yongchun Zhu, Fuzhen Zhuang, Jindong Wang, Guolin Ke, Jingwu Chen, Jiang Bian, Hui Xiong, Qing He:
Deep Subdomain Adaptation Network for Image Classification. IEEE Trans. Neural Networks Learn. Syst. 32(4): 1713-1722 (2021) - [c11]Dongbo Xi, Bowen Song, Fuzhen Zhuang, Yongchun Zhu, Shuai Chen, Tianyi Zhang, Yuan Qi, Qing He:
Modeling the Field Value Variations and Field Interactions Simultaneously for Fraud Detection. AAAI 2021: 14957-14965 - [c10]Qiong Nan, Juan Cao, Yongchun Zhu, Yanyan Wang, Jintao Li:
MDFEND: Multi-domain Fake News Detection. CIKM 2021: 3343-3347 - [c9]Dongbo Xi, Zhen Chen, Peng Yan, Yinger Zhang, Yongchun Zhu, Fuzhen Zhuang, Yu Chen:
Modeling the Sequential Dependence among Audience Multi-step Conversions with Multi-task Learning in Targeted Display Advertising. KDD 2021: 3745-3755 - [c8]Yongchun Zhu, Yudan Liu, Ruobing Xie, Fuzhen Zhuang, Xiaobo Hao, Kaikai Ge, Xu Zhang, Leyu Lin, Juan Cao:
Learning to Expand Audience via Meta Hybrid Experts and Critics for Recommendation and Advertising. KDD 2021: 4005-4013 - [c7]Yongchun Zhu, Ruobing Xie, Fuzhen Zhuang, Kaikai Ge, Ying Sun, Xu Zhang, Leyu Lin, Juan Cao:
Learning to Warm Up Cold Item Embeddings for Cold-start Recommendation with Meta Scaling and Shifting Networks. SIGIR 2021: 1167-1176 - [c6]Yongchun Zhu, Kaikai Ge, Fuzhen Zhuang, Ruobing Xie, Dongbo Xi, Xu Zhang, Leyu Lin, Qing He:
Transfer-Meta Framework for Cross-domain Recommendation to Cold-Start Users. SIGIR 2021: 1813-1817 - [i12]Yongchun Zhu, Fuzhen Zhuang, Xiangliang Zhang, Zhiyuan Qi, Zhiping Shi, Qing He:
Combat Data Shift in Few-shot Learning with Knowledge Graph. CoRR abs/2101.11354 (2021) - [i11]Yongchun Zhu, Kaikai Ge, Fuzhen Zhuang, Ruobing Xie, Dongbo Xi, Xu Zhang, Leyu Lin, Qing He:
Transfer-Meta Framework for Cross-domain Recommendation to Cold-Start Users. CoRR abs/2105.04785 (2021) - [i10]Yongchun Zhu, Ruobing Xie, Fuzhen Zhuang, Kaikai Ge, Ying Sun, Xu Zhang, Leyu Lin, Juan Cao:
Learning to Warm Up Cold Item Embeddings for Cold-start Recommendation with Meta Scaling and Shifting Networks. CoRR abs/2105.04790 (2021) - [i9]Dongbo Xi, Zhen Chen, Peng Yan, Yinger Zhang, Yongchun Zhu, Fuzhen Zhuang, Yu Chen:
Modeling the Sequential Dependence among Audience Multi-step Conversions with Multi-task Learning in Targeted Display Advertising. CoRR abs/2105.08489 (2021) - [i8]Yongchun Zhu, Yudan Liu, Ruobing Xie, Fuzhen Zhuang, Xiaobo Hao, Kaikai Ge, Xu Zhang, Leyu Lin, Juan Cao:
Learning to Expand Audience via Meta Hybrid Experts and Critics for Recommendation and Advertising. CoRR abs/2105.14688 (2021) - [i7]Yongchun Zhu, Fuzhen Zhuang, Jindong Wang, Guolin Ke, Jingwu Chen, Jiang Bian, Hui Xiong, Qing He:
Deep Subdomain Adaptation Network for Image Classification. CoRR abs/2106.09388 (2021) - [i6]Yongchun Zhu, Zhenwei Tang, Yudan Liu, Fuzhen Zhuang, Ruobing Xie, Xu Zhang, Leyu Lin, Qing He:
Personalized Transfer of User Preferences for Cross-domain Recommendation. CoRR abs/2110.11154 (2021) - [i5]Dongbo Xi, Fuzhen Zhuang, Bowen Song, Yongchun Zhu, Shuai Chen, Dan Hong, Tao Chen, Xi Gu, Qing He:
Neural Hierarchical Factorization Machines for User's Event Sequence Analysis. CoRR abs/2112.15292 (2021) - 2020
- [j2]Quan Lu, Ting Liu, Chang Li, Jing Chen, Yongchun Zhu, Shengyi You, Siwei Yu:
Investigation into Information Release of Chinese Government and Departments on COVID-19. Data Inf. Manag. 4(3): 209-235 (2020) - [c5]Dongbo Xi, Fuzhen Zhuang, Bowen Song, Yongchun Zhu, Shuai Chen, Dan Hong, Tao Chen, Xi Gu, Qing He:
Neural Hierarchical Factorization Machines for User's Event Sequence Analysis. SIGIR 2020: 1893-1896 - [c4]Yongchun Zhu, Dongbo Xi, Bowen Song, Fuzhen Zhuang, Shuai Chen, Xi Gu, Qing He:
Modeling Users' Behavior Sequences with Hierarchical Explainable Network for Cross-domain Fraud Detection. WWW 2020: 928-938 - [i4]Dongbo Xi, Fuzhen Zhuang, Yongchun Zhu, Pengpeng Zhao, Xiangliang Zhang, Qing He:
Graph Factorization Machines for Cross-Domain Recommendation. CoRR abs/2007.05911 (2020) - [i3]Dongbo Xi, Bowen Song, Fuzhen Zhuang, Yongchun Zhu, Shuai Chen, Tianyi Zhang, Yuan Qi, Qing He:
Modeling the Field Value Variations and Field Interactions Simultaneously for Fraud Detection. CoRR abs/2008.05600 (2020)
2010 – 2019
- 2019
- [j1]Yongchun Zhu, Fuzhen Zhuang, Jindong Wang, Jingwu Chen, Zhiping Shi, Wenjuan Wu, Qing He:
Multi-representation adaptation network for cross-domain image classification. Neural Networks 119: 214-221 (2019) - [c3]Yongchun Zhu, Fuzhen Zhuang, Deqing Wang:
Aligning Domain-Specific Distribution and Classifier for Cross-Domain Classification from Multiple Sources. AAAI 2019: 5989-5996 - [c2]Yongchun Zhu, Fuzhen Zhuang, Jingyuan Yang, Xi Yang, Qing He:
Adaptively Transfer Category-Classifier for Handwritten Chinese Character Recognition. PAKDD (1) 2019: 110-122 - [i2]Fuzhen Zhuang, Zhiyuan Qi, Keyu Duan, Dongbo Xi, Yongchun Zhu, Hengshu Zhu, Hui Xiong, Qing He:
A Comprehensive Survey on Transfer Learning. CoRR abs/1911.02685 (2019) - [i1]Fuzhen Zhuang, Keyu Duan, Tongjia Guo, Yongchun Zhu, Dongbo Xi, Zhiyuan Qi, Qing He:
Transfer Learning Toolkit: Primers and Benchmarks. CoRR abs/1911.08967 (2019) - 2012
- [c1]Lanzheng Liu, Rui Chu, Yongchun Zhu, Pengfei Zhang, Liufeng Wang:
DMSS: A Dynamic Memory Scheduling System in Server Consolidation Environments. ISORC Workshops 2012: 70-75
Coauthor Index
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last updated on 2024-11-15 20:40 CET by the dblp team
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