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ORCIDLiang Chen 0001
陈亮
Person information
- unicode name: 陈亮
- affiliation: Sun Yat-Sen University, School of Data and Computer Science, Guangzhou, China
- affiliation (former): RMIT University, Melbourne, Australia
- affiliation (PhD 2015): Zhejiang University, College of Computer Science amp; Technology, CCNT, China
- not to be confused with: Liang Chen 0002
Other persons with the same name
- Liang Chen — disambiguation page
- Liang Chen 0002
![[0000-0003-0968-2936]](https://dblp1.uni-trier.de/img/orcid-mark.12x12.png "0000-0003-0968-2936")
— Sun Yat-sen University, School of Communication and Design, Guangzhou, China (and 2 more) - Liang Chen 0003 — Nanjing University of Science and Technology, School of Computer Science and Engineering, China
- Liang Chen 0004 — Beijing Institute of Technology, School of Information and Electronic, China
- Liang Chen 0005 — Huaibei Normal University, School of Mathematical Sciences, China (and 1 more)
- Liang Chen 0006 — Hunan University, College of Mathematics and Econometrics, Changsha, China
- Liang Chen 0007 — Wuhan University, LIEMARS, China (and 3 more)
- Liang Chen 0009 — Shenzhen University, College of Information Engineering, China (and 1 more)
- Liang Chen 0010 — Xidian University, State Key Laboratory of Integrated Service Networks, Xi'an, China
- Liang Chen 0011 — Chongqing College of Electronic Engineering, Electronic Technician Institute, China
- Liang Chen 0012 — Wenzhou University, College of Mathematics and Information Science, China (and 3 more)
- Liang Chen 0013 — Jiangsu Electric Power Company Research Institute, Nanjing, China
- Liang Chen 0014 — Karlsruhe Institute of Technology, Germany
- Liang Chen 0015 — Harbin Institute of Technology, School of Electronics and Information Engineering, Communications Research Center, Harbin, China
- Liang Chen 0016 — Chongqing Medical University, Department of Hepatobiliary Surgery, Chongqing, China
- Liang Chen 0017 — Zhejiang University, Institute of Cyber-Systems and Control, State Key Laboratory of Industrial Control Technology, Hangzhou, China (and 2 more)
- Liang Chen 0018 — Imperial College London, Department of Computing, Biomedical Image Analysis Group, London, UK
- Liang Chen 0019 — Ohio State Uinversity, Department of Computer Science and Engineering, Columbus, OH, USA
- Liang Chen 0020 — King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
- Liang Chen 0021 — Shantou University, Key Laboratory of Intelligent Manufacturing Technology of Ministry of Education, Shantou, China (and 2 more)
- Liang Chen 0022 — Jilin University, College of Computer Science and Technology, MoE Key Laboratory of Symbolic Computation and Knowledge Engineering, Changchun, China
- Liang Chen 0023 — Fudan University, Huashan Hospital, Department of Neurosurgery, Shanghai, China
- Liang Chen 0024 — Peking University, National Key Laboratory for Multimedia Information Processing, China
- Liang Chen 0025 — University of California, Riverside, Department of Electrical and Computer Engineering, CA, USA (and 1 more)
- Liang Chen 0026 — Fujian Normal University, College of Photonic and Electronic Engineering, Fuzhou, China (and 1 more)
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2020 – today
- 2024
[j39]Fenfang Xie, Angyu Zheng, Liang Chen, Zibin Zheng, Mingdong Tang:
Weighted meta-graph based mobile application recommendation through matrix factorisation and neural networks. Connect. Sci. 36(1) (2024)- [c101]Liang Chen, Yatao Bian, Yang Deng, Deng Cai, Shuaiyi Li, Peilin Zhao, Kam-Fai Wong:
WatME: Towards Lossless Watermarking Through Lexical Redundancy. ACL (1) 2024: 9166-9180 - [c100]Yuanzhen Xie, Xinzhou Jin, Tao Xie, Matrixmxlin Matrixmxlin, Liang Chen, Chenyun Yu, Cheng Lei, Chengxiang Zhuo, Bo Hu, Zang Li:
Decomposition for Enhancing Attention: Improving LLM-based Text-to-SQL through Workflow Paradigm. ACL (Findings) 2024: 10796-10816 - [c99]Jintang Li, Huizhe Zhang, Ruofan Wu, Zulun Zhu, Baokun Wang, Changhua Meng, Zibin Zheng, Liang Chen:
A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks. ICLR 2024 - [c98]Yunfei Liu, Jintang Li, Yuehe Chen, Ruofan Wu, Ericbk Wang, Jing Zhou, Sheng Tian, Shuheng Shen, Xing Fu, Changhua Meng, Weiqiang Wang, Liang Chen:
Revisiting Modularity Maximization for Graph Clustering: A Contrastive Learning Perspective. KDD 2024: 1968-1979 - [c97]Yuchang Zhu, Jintang Li, Yatao Bian, Zibin Zheng, Liang Chen:
One Fits All: Learning Fair Graph Neural Networks for Various Sensitive Attributes. KDD 2024: 4688-4699 - [c96]Zezhong Wang, Fangkai Yang, Lu Wang, Pu Zhao, Hongru Wang, Liang Chen, Qingwei Lin, Kam-Fai Wong:
SELF-GUARD: Empower the LLM to Safeguard Itself. NAACL-HLT 2024: 1648-1668 - [c95]Wangbin Sun, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng:
Rethinking and Simplifying Bootstrapped Graph Latents. WSDM 2024: 665-673 - [c94]Yuchang Zhu, Jintang Li, Liang Chen, Zibin Zheng:
The Devil is in the Data: Learning Fair Graph Neural Networks via Partial Knowledge Distillation. WSDM 2024: 1012-1021 - [c93]Yuchang Zhu, Jintang Li, Zibin Zheng, Liang Chen:
Fair Graph Representation Learning via Sensitive Attribute Disentanglement. WWW 2024: 1182-1192 - [i52]Yuanzhen Xie, Xinzhou Jin, Tao Xie, Mingxiong Lin, Liang Chen, Chenyun Yu, Lei Cheng, Chengxiang Zhuo, Bo Hu, Zang Li:
Decomposition for Enhancing Attention: Improving LLM-based Text-to-SQL through Workflow Paradigm. CoRR abs/2402.10671 (2024) - [i51]Shuaiyi Li, Yang Deng, Deng Cai, Hongyuan Lu, Liang Chen, Wai Lam:
Consecutive Model Editing with Batch alongside HooK Layers. CoRR abs/2403.05330 (2024) - [i50]Huizhe Zhang, Jintang Li, Liang Chen, Zibin Zheng:
SGHormer: An Energy-Saving Graph Transformer Driven by Spikes. CoRR abs/2403.17656 (2024) - [i49]Yuchang Zhu, Jintang Li, Zibin Zheng, Liang Chen:
Fair Graph Representation Learning via Sensitive Attribute Disentanglement. CoRR abs/2405.07011 (2024) - [i48]Jintang Li, Ruofan Wu, Xinzhou Jin, Boqun Ma, Liang Chen, Zibin Zheng:
State Space Models on Temporal Graphs: A First-Principles Study. CoRR abs/2406.00943 (2024) - [i47]Yuchang Zhu, Jintang Li, Yatao Bian, Zibin Zheng, Liang Chen:
One Fits All: Learning Fair Graph Neural Networks for Various Sensitive Attributes. CoRR abs/2406.13544 (2024) - [i46]Yunfei Liu, Jintang Li, Yuehe Chen, Ruofan Wu, Ericbk Wang, Jing Zhou, Sheng Tian, Shuheng Shen, Xing Fu, Changhua Meng, Weiqiang Wang, Liang Chen:
Revisiting Modularity Maximization for Graph Clustering: A Contrastive Learning Perspective. CoRR abs/2406.14288 (2024) - [i45]Xinzhou Jin, Jintang Li, Liang Chen, Chenyun Yu, Yuanzhen Xie, Tao Xie, Chengxiang Zhuo, Zang Li, Zibin Zheng:
L2CL: Embarrassingly Simple Layer-to-Layer Contrastive Learning for Graph Collaborative Filtering. CoRR abs/2407.14266 (2024) - 2023
- [j38]Peilin Zheng, Zibin Zheng, Liang Chen:
Selecting reliable blockchain peers via hybrid blockchain reliability prediction. IET Softw. 17(4): 362-377 (2023) - [j37]Jintang Li, Tao Xie, Liang Chen, Fenfang Xie, Xiangnan He, Zibin Zheng:
Adversarial Attack on Large Scale Graph. IEEE Trans. Knowl. Data Eng. 35(1): 82-95 (2023) - [j36]Jintang Li, Jiaying Peng, Liang Chen, Zibin Zheng, Tingting Liang, Qing Ling:
Spectral Adversarial Training for Robust Graph Neural Network. IEEE Trans. Knowl. Data Eng. 35(9): 9240-9253 (2023) - [j35]Tingting Liang, Congying Xia, Haoran Xu, Ziqiang Zhao, Yuyu Yin, Liang Chen, Philip S. Yu:
Modeling Reviews for Few-Shot Recommendation via Enhanced Prototypical Network. IEEE Trans. Knowl. Data Eng. 35(9): 9407-9420 (2023) - [c92]Jintang Li, Zhouxin Yu, Zulun Zhu, Liang Chen, Qi Yu, Zibin Zheng, Sheng Tian, Ruofan Wu, Changhua Meng:
Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks. AAAI 2023: 8588-8596 - [c91]Liang Chen, Hongru Wang, Yang Deng, Wai-Chung Kwan, Zezhong Wang, Kam-Fai Wong:
Towards Robust Personalized Dialogue Generation via Order-Insensitive Representation Regularization. ACL (Findings) 2023: 7337-7345 - [c90]Qichao Wang, Huan Ma, Wentao Wei, Hangyu Li, Changqing Zhang, Peilin Zhao, Binwen Zhao, Bo Hu, Shu Zhang, Bingzhe Wu, Liang Chen:
Attention Paper: How Generative AI Reshapes Digital Shadow Industry? ACM TUR-C 2023: 143-144 - [c89]Jintang Li, Jie Liao, Ruofan Wu, Liang Chen, Zibin Zheng, Jiawang Dan, Changhua Meng, Weiqiang Wang:
GUARD: Graph Universal Adversarial Defense. CIKM 2023: 1198-1207 - [c88]Jie Liao, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng:
SAILOR: Structural Augmentation Based Tail Node Representation Learning. CIKM 2023: 1389-1399 - [c87]Ruoting Wu, Yuxin Zhang, Liang Chen:
Improving Code Representation Learning via Multi-view Contrastive Graph Pooling for Abstract Syntax Tree. CollaborateCom (2) 2023: 242-261 - [c86]Yuxin Zhang, Ruoting Wu, Jie Liao, Liang Chen:
Structural Adversarial Attack for Code Representation Models. CollaborateCom (2) 2023: 392-413 - [c85]Liang Chen, Yang Deng, Yatao Bian, Zeyu Qin, Bingzhe Wu, Tat-Seng Chua, Kam-Fai Wong:
Beyond Factuality: A Comprehensive Evaluation of Large Language Models as Knowledge Generators. EMNLP 2023: 6325-6341 - [c84]Haotian Wang, Zhen Zhang, Mengting Hu, Qichao Wang, Liang Chen, Yatao Bian, Bingzhe Wu:
RECAL: Sample-Relation Guided Confidence Calibration over Tabular Data. EMNLP (Findings) 2023: 7246-7257 - [c83]Yang Deng, Lizi Liao, Liang Chen, Hongru Wang, Wenqiang Lei, Tat-Seng Chua:
Prompting and Evaluating Large Language Models for Proactive Dialogues: Clarification, Target-guided, and Non-collaboration. EMNLP (Findings) 2023: 10602-10621 - [c82]Zishan Gu, Ke Zhang, Guangji Bai, Liang Chen, Liang Zhao, Carl Yang:
Dynamic Activation of Clients and Parameters for Federated Learning over Heterogeneous Graphs. ICDE 2023: 1597-1610 - [c81]Yang Liu, Liang Chen, Xiangnan He, Jiaying Peng, Zibin Zheng, Jie Tang:
Modelling High-Order Social Relations for Item Recommendation (Extended Abstract). ICDE 2023: 3821-3822 - [c80]Xinzhou Jin, Jintang Li, Yuanzhen Xie, Liang Chen, Beibei Kong, Lei Cheng, Bo Hu, Zang Li, Zibin Zheng:
Enhancing Graph Collaborative Filtering via Neighborhood Structure Embedding. ICDM 2023: 190-199 - [c79]Sheng Tian, Jihai Dong, Jintang Li, Wenlong Zhao, Xiaolong Xu, Baokun Wang, Bowen Song, Changhua Meng, Tianyi Zhang, Liang Chen:
SAD: Semi-Supervised Anomaly Detection on Dynamic Graphs. IJCAI 2023: 2306-2314 - [c78]Jintang Li, Ruofan Wu, Wangbin Sun, Liang Chen, Sheng Tian, Liang Zhu, Changhua Meng, Zibin Zheng, Weiqiang Wang:
What's Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders. KDD 2023: 1268-1279 - [c77]Wei Yuan, Quoc Viet Hung Nguyen, Tieke He, Liang Chen, Hongzhi Yin:
Manipulating Federated Recommender Systems: Poisoning with Synthetic Users and Its Countermeasures. SIGIR 2023: 1690-1699 - [i44]Wei Yuan, Quoc Viet Hung Nguyen, Tieke He, Liang Chen, Hongzhi Yin:
Manipulating Federated Recommender Systems: Poisoning with Synthetic Users and Its Countermeasures. CoRR abs/2304.03054 (2023) - [i43]Jintang Li, Sheng Tian, Ruofan Wu, Liang Zhu, Wenlong Zhao, Changhua Meng, Liang Chen, Zibin Zheng, Hongzhi Yin:
Less Can Be More: Unsupervised Graph Pruning for Large-scale Dynamic Graphs. CoRR abs/2305.10673 (2023) - [i42]Liang Chen, Hongru Wang, Yang Deng, Wai-Chung Kwan, Zezhong Wang, Kam-Fai Wong:
Towards Robust Personalized Dialogue Generation via Order-Insensitive Representation Regularization. CoRR abs/2305.12782 (2023) - [i41]Sheng Tian, Jihai Dong, Jintang Li, Wenlong Zhao, Xiaolong Xu, Baokun Wang, Bowen Song, Changhua Meng, Tianyi Zhang, Liang Chen:
SAD: Semi-Supervised Anomaly Detection on Dynamic Graphs. CoRR abs/2305.13573 (2023) - [i40]Qichao Wang, Huan Ma, Wentao Wei, Hangyu Li, Liang Chen, Peilin Zhao, Binwen Zhao, Bo Hu, Shu Zhang, Zibin Zheng, Bingzhe Wu:
Attention Paper: How Generative AI Reshapes Digital Shadow Industry? CoRR abs/2305.18346 (2023) - [i39]Jintang Li, Huizhe Zhang, Ruofan Wu, Zulun Zhu, Liang Chen, Zibin Zheng, Baokun Wang, Changhua Meng:
A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks. CoRR abs/2305.19306 (2023) - [i38]Jintang Li, Wangbin Sun, Ruofan Wu, Yuchang Zhu, Liang Chen, Zibin Zheng:
Scaling Up, Scaling Deep: Blockwise Graph Contrastive Learning. CoRR abs/2306.02117 (2023) - [i37]Jie Liao, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng:
SAILOR: Structural Augmentation Based Tail Node Representation Learning. CoRR abs/2308.06801 (2023) - [i36]Yachuan Liu, Liang Chen, Jindong Wang, Qiaozhu Mei, Xing Xie:
Meta Semantic Template for Evaluation of Large Language Models. CoRR abs/2310.01448 (2023) - [i35]Liang Chen, Yang Deng, Yatao Bian, Zeyu Qin, Bingzhe Wu, Tat-Seng Chua, Kam-Fai Wong:
Beyond Factuality: A Comprehensive Evaluation of Large Language Models as Knowledge Generators. CoRR abs/2310.07289 (2023) - [i34]Jintang Li, Zheng Wei, Jiawang Dan, Jing Zhou, Yuchang Zhu, Ruofan Wu, Baokun Wang, Zhang Zhen, Changhua Meng, Hong Jin, Zibin Zheng, Liang Chen:
Hetero$^2$Net: Heterophily-aware Representation Learning on Heterogenerous Graphs. CoRR abs/2310.11664 (2023) - [i33]Qichao Wang, Tian Bian, Yian Yin, Tingyang Xu, Hong Cheng, Helen M. Meng, Zibin Zheng, Liang Chen, Bingzhe Wu:
Language Agents for Detecting Implicit Stereotypes in Text-to-image Models at Scale. CoRR abs/2310.11778 (2023) - [i32]Zezhong Wang, Fangkai Yang, Lu Wang, Pu Zhao, Hongru Wang, Liang Chen, Qingwei Lin, Kam-Fai Wong:
Self-Guard: Empower the LLM to Safeguard Itself. CoRR abs/2310.15851 (2023) - [i31]Liang Chen, Yatao Bian, Yang Deng, Shuaiyi Li, Bingzhe Wu, Peilin Zhao, Kam-Fai Wong:
X-Mark: Towards Lossless Watermarking Through Lexical Redundancy. CoRR abs/2311.09832 (2023) - [i30]Jintang Li, Jiawang Dan, Ruofan Wu, Jing Zhou, Sheng Tian, Yunfei Liu, Baokun Wang, Changhua Meng, Weiqiang Wang, Yuchang Zhu, Liang Chen, Zibin Zheng:
LasTGL: An Industrial Framework for Large-Scale Temporal Graph Learning. CoRR abs/2311.16605 (2023) - [i29]Hongru Wang, Lingzhi Wang, Yiming Du, Liang Chen, Jingyan Zhou, Yufei Wang, Kam-Fai Wong:
A Survey of the Evolution of Language Model-Based Dialogue Systems. CoRR abs/2311.16789 (2023) - [i28]Yuchang Zhu, Jintang Li, Liang Chen, Zibin Zheng:
The Devil is in the Data: Learning Fair Graph Neural Networks via Partial Knowledge Distillation. CoRR abs/2311.17373 (2023) - [i27]Wangbin Sun, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng:
Rethinking and Simplifying Bootstrapped Graph Latents. CoRR abs/2312.02619 (2023) - 2022
- [j34]Fenfang Xie, Yangjun Xu, Angyu Zheng, Liang Chen, Zibin Zheng:
Service recommendation through graph attention network in heterogeneous information networks. Int. J. Comput. Sci. Eng. 25(6): 643-656 (2022) - [j33]Liang Chen, Tao Xie, Jintang Li, Zibin Zheng:
Graph Enhanced Neural Interaction Model for recommendation. Knowl. Based Syst. 246: 108616 (2022) - [j32]Zhouxin Yu, Jintang Li, Liang Chen, Zibin Zheng:
Unifying multi-associations through hypergraph for bundle recommendation. Knowl. Based Syst. 255: 109755 (2022) - [j31]Yang Liu, Liang Chen, Xiangnan He, Jiaying Peng, Zibin Zheng, Jie Tang:
Modelling High-Order Social Relations for Item Recommendation. IEEE Trans. Knowl. Data Eng. 34(9): 4385-4397 (2022) - [j30]Minghao Zhao, Qilin Deng, Kai Wang, Runze Wu, Jianrong Tao, Changjie Fan, Liang Chen, Peng Cui:
Bilateral Filtering Graph Convolutional Network for Multi-relational Social Recommendation in the Power-law Networks. ACM Trans. Inf. Syst. 40(2): 31:1-31:24 (2022) - [c76]Zulun Zhu, Jiaying Peng, Jintang Li, Liang Chen, Qi Yu, Siqiang Luo:
Spiking Graph Convolutional Networks. IJCAI 2022: 2434-2440 - [c75]Bingzhe Wu, Yatao Bian, Hengtong Zhang, Jintang Li, Junchi Yu, Liang Chen, Chaochao Chen, Junzhou Huang:
Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection. KDD 2022: 4838-4839 - [i26]Liang Chen, Qibiao Peng, Jintang Li, Yang Liu, Jiawei Chen, Yong Li, Zibin Zheng:
Neighboring Backdoor Attacks on Graph Convolutional Network. CoRR abs/2201.06202 (2022) - [i25]Bingzhe Wu, Jintang Li, Chengbin Hou, Guoji Fu, Yatao Bian, Liang Chen, Junzhou Huang:
Recent Advances in Reliable Deep Graph Learning: Adversarial Attack, Inherent Noise, and Distribution Shift. CoRR abs/2202.07114 (2022) - [i24]Jintang Li, Jie Liao, Ruofan Wu, Liang Chen, Changhua Meng, Zibin Zheng, Weiqiang Wang:
GUARD: Graph Universal Adversarial Defense. CoRR abs/2204.09803 (2022) - [i23]Yuansheng Wang, Wangbin Sun, Kun Xu, Zulun Zhu, Liang Chen, Zibin Zheng:
FastGCL: Fast Self-Supervised Learning on Graphs via Contrastive Neighborhood Aggregation. CoRR abs/2205.00905 (2022) - [i22]Ruoting Wu, Yuxin Zhang, Qibiao Peng, Liang Chen, Zibin Zheng:
A Survey of Deep Learning Models for Structural Code Understanding. CoRR abs/2205.01293 (2022) - [i21]Zulun Zhu, Jiaying Peng, Jintang Li, Liang Chen, Qi Yu, Siqiang Luo:
Spiking Graph Convolutional Networks. CoRR abs/2205.02767 (2022) - [i20]Bingzhe Wu, Jintang Li, Junchi Yu, Yatao Bian, Hengtong Zhang, Chaochao Chen, Chengbin Hou, Guoji Fu, Liang Chen, Tingyang Xu, Yu Rong, Xiaolin Zheng, Junzhou Huang, Ran He, Baoyuan Wu, Guangyu Sun, Peng Cui, Zibin Zheng, Zhe Liu, Peilin Zhao:
A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection. CoRR abs/2205.10014 (2022) - [i19]Jintang Li, Ruofan Wu, Wangbin Sun, Liang Chen, Sheng Tian, Liang Zhu, Changhua Meng, Zibin Zheng, Weiqiang Wang:
MaskGAE: Masked Graph Modeling Meets Graph Autoencoders. CoRR abs/2205.10053 (2022) - [i18]Jintang Li, Zhouxin Yu, Zulun Zhu, Liang Chen, Qi Yu, Zibin Zheng, Sheng Tian, Ruofan Wu, Changhua Meng:
Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks. CoRR abs/2208.10364 (2022) - [i17]Zishan Gu, Jintang Li, Liang Chen:
Are All Edges Necessary? A Unified Framework for Graph Purification. CoRR abs/2211.05184 (2022) - [i16]Jintang Li, Jiaying Peng, Liang Chen, Zibin Zheng, Tingting Liang, Qing Ling:
Spectral Adversarial Training for Robust Graph Neural Network. CoRR abs/2211.10896 (2022) - 2021
- [j29]Tingting Liang, Xuan Sheng, Li Zhou, Youhuizi Li, Honghao Gao, Yuyu Yin, Liang Chen:
Mobile app recommendation via heterogeneous graph neural network in edge computing. Appl. Soft Comput. 103: 107162 (2021) - [j28]Liang Chen, Yangjun Xu, Fenfang Xie, Min Huang, Zibin Zheng:
Data poisoning attacks on neighborhood-based recommender systems. Trans. Emerg. Telecommun. Technol. 32(6) (2021) - [j27]Fenfang Xie, Angyu Zheng, Liang Chen, Zibin Zheng:
Attentive Meta-graph Embedding for item Recommendation in heterogeneous information networks. Knowl. Based Syst. 211: 106524 (2021) - [j26]Liang Chen, Jiaying Peng, Yang Liu, Jintang Li, Fenfang Xie, Zibin Zheng:
Phishing Scams Detection in Ethereum Transaction Network. ACM Trans. Internet Techn. 21(1): 10:1-10:16 (2021) - [c74]Kai Wang, Zhene Zou, Qilin Deng, Jianrong Tao, Runze Wu, Changjie Fan, Liang Chen, Peng Cui:
Reinforcement Learning with a Disentangled Universal Value Function for Item Recommendation. AAAI 2021: 4427-4435 - [c73]Kun Xu, Yuanzhen Xie, Liang Chen, Zibin Zheng:
Expanding Relationship for Cross Domain Recommendation. CIKM 2021: 2251-2260 - [c72]Tao Xie, Yangjun Xu, Liang Chen, Yang Liu, Zibin Zheng:
Sequential Recommendation on Dynamic Heterogeneous Information Network. ICDE 2021: 2105-2110 - [c71]Jintang Li, Kun Xu, Liang Chen, Zibin Zheng, Xiao Liu:
GraphGallery: A Platform for Fast Benchmarking and Easy Development of Graph Neural Networks Based Intelligent Software. ICSE (Companion Volume) 2021: 13-16 - [c70]Liang Chen, Jintang Li, Qibiao Peng, Yang Liu, Zibin Zheng, Carl Yang:
Understanding Structural Vulnerability in Graph Convolutional Networks. IJCAI 2021: 2249-2255 - [c69]Carl Yang, Haonan Wang, Ke Zhang, Liang Chen, Lichao Sun:
Secure Deep Graph Generation with Link Differential Privacy. IJCAI 2021: 3271-3278 - [c68]Jiawei Chen, Hande Dong, Yang Qiu, Xiangnan He, Xin Xin, Liang Chen, Guli Lin, Keping Yang:
AutoDebias: Learning to Debias for Recommendation. SIGIR 2021: 21-30 - [c67]Jiancan Wu, Xiang Wang, Fuli Feng, Xiangnan He, Liang Chen, Jianxun Lian, Xing Xie:
Self-supervised Graph Learning for Recommendation. SIGIR 2021: 726-735 - [c66]Yuanzhen Xie, Zijing Ou, Liang Chen, Yang Liu, Kun Xu, Carl Yang, Zibin Zheng:
Learning and Updating Node Embedding on Dynamic Heterogeneous Information Network. WSDM 2021: 184-192 - [c65]Yu Zheng, Chen Gao, Liang Chen, Depeng Jin, Yong Li:
DGCN: Diversified Recommendation with Graph Convolutional Networks. WWW 2021: 401-412 - [i15]Jintang Li, Kun Xu, Liang Chen, Zibin Zheng, Xiao Liu:
GraphGallery: A Platform for Fast Benchmarking and Easy Development of Graph Neural Networks Based Intelligent Software. CoRR abs/2102.07933 (2021) - [i14]Kai Wang, Zhene Zou, Qilin Deng, Runze Wu, Jianrong Tao, Changjie Fan, Liang Chen, Peng Cui:
Reinforcement Learning with a Disentangled Universal Value Function for Item Recommendation. CoRR abs/2104.02981 (2021) - [i13]Qilin Deng, Kai Wang, Minghao Zhao, Zhene Zou, Runze Wu, Jianrong Tao, Changjie Fan, Liang Chen:
Personalized Bundle Recommendation in Online Games. CoRR abs/2104.05307 (2021) - [i12]Jiawei Chen, Hande Dong, Yang Qiu, Xiangnan He, Xin Xin, Liang Chen, Guli Lin, Keping Yang:
AutoDebias: Learning to Debias for Recommendation. CoRR abs/2105.04170 (2021) - [i11]Liang Chen, Jintang Li, Qibiao Peng, Yang Liu, Zibin Zheng, Carl Yang:
Understanding Structural Vulnerability in Graph Convolutional Networks. CoRR abs/2108.06280 (2021) - [i10]Yu Zheng, Chen Gao, Liang Chen, Depeng Jin, Yong Li:
DGCN: Diversified Recommendation with Graph Convolutional Networks. CoRR abs/2108.06952 (2021) - 2020
- [j25]Liang Chen, Yuanzhen Xie, Zibin Zheng, Huayou Zheng, Jingdun Xie:
Friend Recommendation Based on Multi-Social Graph Convolutional Network. IEEE Access 8: 43618-43629 (2020) - [j24]Huakun Huang, Shuxue Ding, Lingjun Zhao, Huawei Huang, Liang Chen, Honghao Gao, Syed Hassan Ahmed:
Real-Time Fault Detection for IIoT Facilities Using GBRBM-Based DNN. IEEE Internet Things J. 7(7): 5713-5722 (2020) - [j23]Tingting Liang, Lifang He, Chun-Ta Lu, Liang Chen, Haochao Ying, Philip S. Yu, Jian Wu:
CAMAR: a broad learning based context-aware recommender for mobile applications. Knowl. Inf. Syst. 62(8): 3291-3319 (2020) - [j22]Tingting Liang, Lei Zheng, Liang Chen, Yao Wan, Philip S. Yu, Jian Wu:
Multi-view factorization machines for mobile app recommendation based on hierarchical attention. Knowl. Based Syst. 187 (2020) - [j21]Bin Wu, Xiangnan He, Zhongchuan Sun, Liang Chen, Yangdong Ye:
ATM: An Attentive Translation Model for Next-Item Recommendation. IEEE Trans. Ind. Informatics 16(3): 1448-1459 (2020) - [j20]Liang Chen, Yongjian Ye, Angyu Zheng, Fenfang Xie, Zibin Zheng, Michael R. Lyu:
Incorporating geographical location for team formation in social coding sites. World Wide Web 23(1): 153-174 (2020) - [c64]Fenfang Xie, Zengxu Cao, Yangjun Xu, Liang Chen, Zibin Zheng:
Graph Neural Network and Multi-view Learning Based Mobile Application Recommendation in Heterogeneous Graphs. SCC 2020: 100-107 - [c63]Qilin Deng, Kai Wang, Minghao Zhao, Zhene Zou, Runze Wu, Jianrong Tao, Changjie Fan, Liang Chen:
Personalized Bundle Recommendation in Online Games. CIKM 2020: 2381-2388 - [c62]Kai Wang, Hao Li, Linxia Gong, Jianrong Tao, Runze Wu, Changjie Fan, Liang Chen, Peng Cui:
Match Tracing: A Unified Framework for Real-time Win Prediction and Quantifiable Performance Evaluation. CIKM 2020: 2781-2788 - [c61]Runze Wu, Hao Deng, Jianrong Tao, Changjie Fan, Qi Liu, Liang Chen:
Deep Behavior Tracing with Multi-level Temporality Preserved Embedding. CIKM 2020: 2813-2820 - [c60]Jieming Zhu, Jinyang Liu, Weiqi Li, Jincai Lai, Xiuqiang He, Liang Chen, Zibin Zheng:
Ensembled CTR Prediction via Knowledge Distillation. CIKM 2020: 2941-2958 - [c59]