Construct SaaS Applications from Multi-abstract-level: Method and System. - Lei Wu 002; Ying Pan; Shijun Liu; Qian Li 003 (ChinaGrid, 2012)

A cooperative construction approach for SaaS applications. - Qian Li 003; Shijun Liu; Ying Pan (CSCWD, 2012)

Comparative Analysis of Clustering Protocols with Probabilistic Model Checking. - Qian Li 003; Péter Schaffer; Jun Pang 001; Sjouke Mauw (TASE, 2012)

A block-aware hybrid data dissemination with hotspot elimination in wireless sensor network. - Wenjia Niu; Gang Li 009; Endong Tong; Quan Z. Sheng; Qian Li 003; Yue Hu 002; Athanasios V. Vasilakos; Li Guo 001 (J. Netw. Comput. Appl., 2014)

Lingo: Linearized Grassmannian Optimization for Nuclear Norm Minimization. - Qian Li 003; Wenjia Niu; Gang Li 009; Yanan Cao 001; Jianlong Tan; Li Guo 001 (CIKM, 2015)

Recover Fault Services via Complex Service-to-Node Mappings in Wireless Sensor Networks. - Qian Li 003; Wenjia Niu; Gang Li 009; Endong Tong; Yue Hu 002; Ping Liu 001; Li Guo 001 (J. Netw. Syst. Manag., 2015)

Riemannian optimization with subspace tracking for low-rank recovery. - Qian Li 003; Wenjia Niu; Gang Li 009; Jianlong Tan; Gang Xiong 001; Li Guo 001 (IJCNN, 2016)

Exploring probabilistic follow relationship to prevent collusive peer-to-peer piracy. - Wenjia Niu; Endong Tong; Qian Li 003; Gang Li 009; Xuemin Wen; Jianlong Tan; Li Guo 001 (Knowl. Inf. Syst., 2016)

Riemannian Submanifold Tracking on Low-Rank Algebraic Variety. - Qian Li 003; Zhichao Wang 001 (AAAI, 2017)

Learning Robust Low-Rank Approximation for Crowdsourcing on Riemannian Manifold. - Qian Li 003; Zhichao Wang 001; Gang Li 009; Yanan Cao 001; Gang Xiong 001; Li Guo 001 (ICCS, 2017)

Boosting imbalanced data learning with Wiener process oversampling. - Qian Li 003; Gang Li 009; Wenjia Niu; Yanan Cao 001; Liang Chang 003; Jianlong Tan; Li Guo 001 (Frontiers Comput. Sci., 2017)

Prediction and Analysis of Rumour's Impact on Social Media. - Jun Yin 005; Shaowu Liu; Qian Li 003; Guandong Xu (BESC, 2019)

Polynomial Representation for Persistence Diagram. - Zhichao Wang 001; Qian Li 003; Gang Li 009; Guandong Xu (CVPR, 2019)

Joint Entity Linking with Deep Reinforcement Learning. - Zheng Fang 002; Yanan Cao 001; Qian Li 003; Dongjie Zhang; Zhenyu Zhang 006; Yanbing Liu (WWW, 2019)

Joint Relational Dependency Learning for Sequential Recommendation. - Xiangmeng Wang; Qian Li 003; Wu Zhang; Guandong Xu; Shaowu Liu; Wenhao Zhu (PAKDD (1), 2020)

Causality Learning: A New Perspective for Interpretable Machine Learning. - Guandong Xu; Tri Dung Duong; Qian Li 003; Shaowu Liu; Xianzhi Wang 001 (CoRR, 2020)

Learning with privileged information for photo aesthetic assessment. - Yangyang Shu; Qian Li 003; Shaowu Liu; Guandong Xu (Neurocomputing, 2020)

Harnessing Privileged Information for Hyperbole Detection. - Rhys Biddle; Maciek Rybinski; Qian Li 003; Cécile Paris; Guandong Xu (ALTA, 2021)

Causal-Aware Generative Imputation for Automated Underwriting. - Qian Li 003; Tri Dung Duong; Zhichao Wang 001; Shaowu Liu; Dingxian Wang; Guandong Xu (CIKM, 2021)

Hilbert Sinkhorn Divergence for Optimal Transport. - Qian Li 003; Zhichao Wang 001; Gang Li 009; Jun Pang 001; Guandong Xu (CVPR, 2021)

Stochastic Intervention for Causal Effect Estimation. - Tri Dung Duong; Qian Li 003; Guandong Xu (IJCNN, 2021)

Prototype-based Counterfactual Explanation for Causal Classification. - Tri Dung Duong; Qian Li 003; Guandong Xu (CoRR, 2021)

Be Causal: De-biasing Social Network Confounding in Recommendation. - Qian Li 003; Xiangmeng Wang; Guandong Xu (CoRR, 2021)

Leveraging multi-level dependency of relational sequences for social spammer detection. - Jun Yin 005; Qian Li 003; Shaowu Liu; Zhiang Wu 001; Guandong Xu (Neurocomputing, 2021)

Reward Space Noise for Exploration in Deep Reinforcement Learning. - Chuxiong Sun; Rui Wang 079; Qian Li 003; Xiaohui Hu (Int. J. Pattern Recognit. Artif. Intell., 2021)

RLINK: Deep reinforcement learning for user identity linkage. - Xiaoxue Li; Yanan Cao 001; Qian Li 003; Yanmin Shang; Yangxi Li; Yanbing Liu; Guandong Xu (World Wide Web, 2021)

How Does Knowledge Graph Embedding Extrapolate to Unseen Data: A Semantic Evidence View. - Ren Li; Yanan Cao 001; Qiannan Zhu; Guanqun Bi; Fang Fang 009; Yi Liu 067; Qian Li 003 (AAAI, 2022)

Task-level Relations Modelling for Graph Meta-learning. - Yuchen Zhou; Yanan Cao 001; Yanmin Shang; Chuan Zhou 001; Chuancheng Song; Fengzhao Shi; Qian Li 003 (ICDM, 2022)

Semantics-Guided Disentangled Learning for Recommendation. - Dianer Yu; Qian Li 003; Xiangmeng Wang; Zhichao Wang 001; Yanan Cao 001; Guandong Xu (PAKDD (1), 2022)

MGPolicy: Meta Graph Enhanced Off-policy Learning for Recommendations. - Xiangmeng Wang; Qian Li 003; Dianer Yu; Zhichao Wang 001; Hongxu Chen 002; Guandong Xu (SIGIR, 2022)

Off-policy Learning over Heterogeneous Information for Recommendation. - Xiangmeng Wang; Qian Li 003; Dianer Yu; Guandong Xu (WWW, 2022)

Causal Disentanglement for Semantics-Aware Intent Learning in Recommendation. - Xiangmeng Wang; Qian Li 003; Dianer Yu; Peng Cui 001; Zhichao Wang 001; Guandong Xu (CoRR, 2022)

Generating Counterfactual Hard Negative Samples for Graph Contrastive Learning. - Haoran Yang; Hongxu Chen 002; Sixiao Zhang; Xiangguo Sun; Qian Li 003; Guandong Xu (CoRR, 2022)

Reinforced Path Reasoning for Counterfactual Explainable Recommendation. - Xiangmeng Wang; Qian Li 003; Dianer Yu; Guandong Xu (CoRR, 2022)

Stochastic intervention for causal inference via reinforcement learning. - Tri Dung Duong; Qian Li 003; Guandong Xu (Neurocomputing, 2022)

Privileged multi-task learning for attribute-aware aesthetic assessment. - Yangyang Shu; Qian Li 003; Lingqiao Liu; Guandong Xu (Pattern Recognit., 2022)

V-SVR+: Support Vector Regression With Variational Privileged Information. - Yangyang Shu; Qian Li 003; Chang Xu 002; Shaowu Liu; Guandong Xu (IEEE Trans. Multim., 2022)

Deep treatment-adaptive network for causal inference. - Qian Li 003; Zhichao Wang 001; Shaowu Liu; Gang Li 009; Guandong Xu (VLDB J., 2022)

API-GNN: attribute preserving oriented interactive graph neural network. - Yuchen Zhou; Yanmin Shang; Yanan Cao 001; Qian Li 003; Chuan Zhou 001; Guandong Xu (World Wide Web, 2022)

Causality-guided Graph Learning for Session-based Recommendation. - Dianer Yu; Qian Li 003; Hongzhi Yin; Guandong Xu (CIKM, 2023)

Dynamic Communications Network Linking Prediction by Disseminating Event Embedding. - Han Cheng; Qian Li 003; Zhihong Cui; Shijun Liu; Li Pan 001 (ICWS, 2023)

CeFlow: A Robust and Efficient Counterfactual Explanation Framework for Tabular Data Using Normalizing Flows. - Tri Dung Duong; Qian Li 003; Guandong Xu (PAKDD (2), 2023)

Toward Explainable Recommendation via Counterfactual Reasoning. - Haiyang Xia; Qian Li 003; Zhichao Wang 001; Gang Li 009 (PAKDD (3), 2023)

SGCCL: Siamese Graph Contrastive Consensus Learning for Personalized Recommendation. - Boyu Li 003; Ting Guo; Xingquan Zhu 001; Qian Li 003; Yang Wang 002; Fang Chen 001 (WSDM, 2023)

Generating Counterfactual Hard Negative Samples for Graph Contrastive Learning. - Haoran Yang; Hongxu Chen 002; Sixiao Zhang; Xiangguo Sun; Qian Li 003; Xiangyu Zhao 001; Guandong Xu (WWW, 2023)

Causal Neural Graph Collaborative Filtering. - Xiangmeng Wang; Qian Li 003; Dianer Yu; Wei Huang; Guandong Xu (CoRR, 2023)

Be Causal: De-Biasing Social Network Confounding in Recommendation. - Qian Li 003; Xiangmeng Wang; Zhichao Wang 001; Guandong Xu (ACM Trans. Knowl. Discov. Data, 2023)

Deconfounded recommendation via causal intervention. - Dianer Yu; Qian Li 003; Xiangmeng Wang; Guandong Xu (Neurocomputing, 2023)

Heterogeneous graphlets-guided network embedding via eulerian-trail-based representation. - Guangxu Mei; Siyuan Ye; Shijun Liu; Li Pan 001; Qian Li 003 (Inf. Sci., 2023)

How the four-nodes motifs work in heterogeneous node representation? - Siyuan Ye; Qian Li 003; Guangxu Mei; Shijun Liu; Li Pan 001 (World Wide Web (WWW), 2023)

Causal Optimal Transport for Treatment Effect Estimation. - Qian Li 003; Zhichao Wang 001; Shaowu Liu; Gang Li 009; Guandong Xu (IEEE Trans. Neural Networks Learn. Syst., 2023)

Causal Disentanglement for Semantic-Aware Intent Learning in Recommendation. - Xiangmeng Wang; Qian Li 003; Dianer Yu; Peng Cui 001; Zhichao Wang 001; Guandong Xu (IEEE Trans. Knowl. Data Eng., 2023)

Explainable Hyperbolic Temporal Point Process for User-Item Interaction Sequence Generation. - Yuchen Zhou; Yanan Cao 001; Yanmin Shang; Chuan Zhou 001; Shirui Pan; Zheng Lin 001; Qian Li 003 (ACM Trans. Inf. Syst., 2023)

Counterfactual Debasing for Multi-behavior Recommendations. - Sirui Huang; Qian Li 003; Xiangmeng Wang; Dianer Yu; Guandong Xu; Qing Li 001 (DASFAA (3), 2024)

Graph Neural Networks for Vulnerability Detection: A Counterfactual Explanation. - Zhaoyang Chu; Yao Wan 001; Qian Li 003; Yang Wu 010; Hongyu Zhang 002; Yulei Sui; Guandong Xu; Hai Jin 001 (ISSTA, 2024)

Achieving counterfactual fairness with imperfect structural causal model. - Tri Dung Duong; Qian Li 003; Guandong Xu (Expert Syst. Appl., 2024)

Neural Causal Graph collaborative filtering. - Xiangmeng Wang; Qian Li 003; Dianer Yu; Wei Huang; Qing Li 001; Guandong Xu (Inf. Sci., 2024)

Causality-based counterfactual explanation for classification models. - Tri Dung Duong; Qian Li 003; Guandong Xu (Knowl. Based Syst., 2024)

Semi-Supervised Adversarial Learning for Attribute-Aware Photo Aesthetic Assessment. - Yangyang Shu; Qian Li 003; Lingqiao Liu; Guandong Xu (IEEE Trans. Multim., 2024)

DGERCL: A Dynamic Graph Embedding Approach for Root Cause Localization in Microservice Systems. - Han Cheng; Qian Li 003; Bingchen Liu; Shijun Liu; Li Pan 001 (IEEE Trans. Serv. Comput., 2024)

Counterfactual Explainable Conversational Recommendation. - Dianer Yu; Qian Li 003; Xiangmeng Wang; Qing Li 001; Guandong Xu (IEEE Trans. Knowl. Data Eng., 2024)

Reinforced Path Reasoning for Counterfactual Explainable Recommendation. - Xiangmeng Wang; Qian Li 003; Dianer Yu; Qing Li 001; Guandong Xu (IEEE Trans. Knowl. Data Eng., 2024)

Counterfactual Explanation for Fairness in Recommendation. - Xiangmeng Wang; Qian Li 003; Dianer Yu; Qing Li 001; Guandong Xu (ACM Trans. Inf. Syst., 2024)

LIHAN: A Lattice-Guided Incomplete Heterogeneous Information Network Embedding Model for Node Classification. - Guangxu Mei; Ziyu Guo; Li Pan 001; Qian Li 003; Feng Li 030; Shijun Liu (IEEE Trans. Comput. Soc. Syst., 2024)

Constrained Off-policy Learning over Heterogeneous Information for Fairness-aware Recommendation. - Xiangmeng Wang; Qian Li 003; Dianer Yu; Qing Li 001; Guandong Xu (Trans. Recomm. Syst., 2024)

Long-term river flow forecasting: An integrated deep learning model with multi-scale feature extraction. - Deguang Wang; Qian Li 003; Shijun Liu; Li Pan 001; Jun Li (Expert Syst. Appl., 2025)

HOT-GAN: Hilbert Optimal Transport for Generative Adversarial Network. - Qian Li 003; Zhichao Wang 001; Haiyang Xia; Gang Li 009; Yanan Cao 001; Lina Yao 001; Guandong Xu (IEEE Trans. Neural Networks Learn. Syst., 2025)

A Causal-Based Attribute Selection Strategy for Conversational Recommender Systems. - Dianer Yu; Qian Li 003; Xiangmeng Wang; Guandong Xu (IEEE Trans. Knowl. Data Eng., 2025)

Contrastive Modality-Disentangled Learning for Multimodal Recommendation. - Xixun Lin; Rui Liu 032; Yanan Cao 001; Lixin Zou; Qian Li 003; Yongxuan Wu; Yang Liu 320; Dawei Yin; Guandong Xu (ACM Trans. Inf. Syst., 2025)