kNN Algorithm with Data-Driven k Value. - Debo Cheng; Shichao Zhang 001; Zhenyun Deng; Yonghua Zhu; Ming Zong (ADMA, 2014)

Improved Spectral Clustering Algorithm Based on Similarity Measure. - Jun Yan; Debo Cheng; Ming Zong; Zhenyun Deng (ADMA, 2014)

Efficient kNN Algorithm Based on Graph Sparse Reconstruction. - Shichao Zhang 001; Ming Zong; Ke Sun 004; Yue Liu; Debo Cheng (ADMA, 2014)

Hypergraph Spectral Clustering via Sample Self-Representation. - Shichao Zhang 001; Yonggang Li; Debo Cheng; Zhen-Yun Deng (FSDM, 2016)

Efficient kNN classification algorithm for big data. - Zhenyun Deng; Xiaoshu Zhu; Debo Cheng; Ming Zong; Shichao Zhang 001 (Neurocomputing, 2016)

Self-representation nearest neighbor search for classification. - Shichao Zhang 001; Debo Cheng; Ming Zong; Lianli Gao (Neurocomputing, 2016)

Graph feature selection for dementia diagnosis. - Yonghua Zhu; Zhi Zhong; Wenfei Cao; Debo Cheng (Neurocomputing, 2016)

Unsupervised feature selection for visual classification via feature-representation property. - Wei He 017; Xiaofeng Zhu 001; Debo Cheng; Rongyao Hu; Shichao Zhang 001 (Neurocomputing, 2017)

Self-representation dimensionality reduction for multi-model classification. - Rongyao Hu; Jie Cao 001; Debo Cheng; Wei He 017; Yonghua Zhu; Qing Xie 002; Guoqiu Wen (Neurocomputing, 2017)

Graph self-representation method for unsupervised feature selection. - Rongyao Hu; Xiaofeng Zhu 001; Debo Cheng; Wei He 017; Yan Yan 002; Jingkuan Song; Shichao Zhang 001 (Neurocomputing, 2017)

Feature selection by combining subspace learning with sparse representation. - Debo Cheng; Shichao Zhang 001; Xingyi Liu; Ke Sun 004; Ming Zong (Multim. Syst., 2017)

Low-rank unsupervised graph feature selection via feature self-representation. - Wei He 017; Xiaofeng Zhu 001; Debo Cheng; Rongyao Hu; Shichao Zhang 001 (Multim. Tools Appl., 2017)

Low-rank feature selection for multi-view regression. - Rongyao Hu; Debo Cheng; Wei He 017; Guoqiu Wen; Yonghua Zhu; Jilian Zhang; Shichao Zhang 001 (Multim. Tools Appl., 2017)

Spectral clustering based on hypergraph and self-re-presentation. - Yonggang Li; Shichao Zhang 001; Debo Cheng; Wei He 017; Guoqiu Wen; Qing Xie 002 (Multim. Tools Appl., 2017)

Leverage triple relational structures via low-rank feature reduction for multi-output regression. - Shichao Zhang 001; Lifeng Yang; Zhenyun Deng; Debo Cheng; Yonggang Li (Multim. Tools Appl., 2017)

Double sparse-representation feature selection algorithm for classification. - Yonghua Zhu; Xuejun Zhang; Guoqiu Wen; Wei He 017; Debo Cheng (Multim. Tools Appl., 2017)

Learning k for kNN Classification. - Shichao Zhang 001; Xuelong Li 001; Ming Zong; Xiaofeng Zhu 001; Debo Cheng (ACM Trans. Intell. Syst. Technol., 2017)

Sparse sample self-representation for subspace clustering. - Zhenyun Deng; Shichao Zhang 001; Lifeng Yang; Ming Zong; Debo Cheng (Neural Comput. Appl., 2018)

Efficient subspace clustering based on self-representation and grouping effect. - Shichao Zhang 001; Yonggang Li; Debo Cheng; Zhenyun Deng; Lifeng Yang (Neural Comput. Appl., 2018)

A novel kNN algorithm with data-driven k parameter computation. - Shichao Zhang 001; Debo Cheng; Zhenyun Deng; Ming Zong; Xuelian Deng (Pattern Recognit. Lett., 2018)

Supervised feature selection algorithm via discriminative ridge regression. - Shichao Zhang 001; Debo Cheng; Rongyao Hu; Zhenyun Deng (World Wide Web, 2018)

Causal Query in Observational Data with Hidden Variables. - Debo Cheng; Jiuyong Li; Lin Liu 003; Jixue Liu; Kui Yu; Thuc Duy Le (ECAI, 2020)

Towards precise causal effect estimation from data with hidden variables. - Debo Cheng; Jiuyong Li; Lin Liu 003; Kui Yu; Thuc Duy Le; Jixue Liu (CoRR, 2020)

Sufficient Dimension Reduction for Average Causal Effect Estimation. - Debo Cheng; Jiuyong Li; Lin Liu 003; Jixue Liu (CoRR, 2020)

Assessing the Fairness of Classifiers with Collider Bias. - Zhenlong Xu; Jixue Liu; Debo Cheng; Jiuyong Li; Lin Liu 003; Ke Wang 001 (CoRR, 2020)

Dynamic Semantic Modeling of Structural Data Sources. - Hailong Chu; Weiming Wu; Wolfgang Mayer; Debo Cheng; Hong-Yu Zhang; Zaiwen Feng (HPCC/DSS/SmartCity/DependSys, 2022)

Stable Causal Feature Selection based on Direct Causal Effect Estimation. - Xiaojing Du; Qingfeng Chen; Debo Cheng; Qian Huang; Junyue Cao; Zhenyun Deng; Shichao Zhang 001 (HPCC/DSS/SmartCity/DependSys, 2022)

Matching Using Sufficient Dimension Reduction for Heterogeneity Causal Effect Estimation. - Haoran Zhao; Yinghao Zhang; Debo Cheng; Chen Li 027; Zaiwen Feng (HPCC/DSS/SmartCity/DependSys, 2022)

Ancestral Instrument Method for Causal Inference without Complete Knowledge. - Debo Cheng; Jiuyong Li; Lin Liu 003; Jiji Zhang; Thuc Duy Le; Jixue Liu (IJCAI, 2022)

Information Augmentation for Few-shot Node Classification. - Zongqian Wu; Peng Zhou 006; Guoqiu Wen; Yingying Wan; Junbo Ma; Debo Cheng; Xiaofeng Zhu 001 (IJCAI, 2022)

Assessing Classifier Fairness with Collider Bias. - Zhenlong Xu; Ziqi Xu 001; Jixue Liu; Debo Cheng; Jiuyong Li; Lin Liu 003; Ke Wang 001 (PAKDD (2), 2022)

Ancestral instrument method for causal inference without a causal graph. - Debo Cheng; Jiuyong Li; Lin Liu 003; Jiji Zhang; Thuc Duy Le; Jixue Liu (CoRR, 2022)

Sufficient dimension reduction for average causal effect estimation. - Debo Cheng; Jiuyong Li; Lin Liu 003; Thuc Duy Le; Jixue Liu; Kui Yu (Data Min. Knowl. Discov., 2022)

Causal Inference with Conditional Instruments Using Deep Generative Models. - Debo Cheng; Ziqi Xu 001; Jiuyong Li; Lin Liu 003; Jixue Liu; Thuc Duy Le (AAAI, 2023)

Disentangled Representation for Causal Mediation Analysis. - Ziqi Xu 001; Debo Cheng; Jiuyong Li; Jixue Liu; Lin Liu 003; Ke Wang 001 (AAAI, 2023)

Multi-head Similarity Feature Representation and Filtration for Image-Text Matching. - Mengqi Jiang; Shichao Zhang 001; Debo Cheng; Leyuan Zhang; Guixian Zhang (ADMA (2), 2023)

Multi-branch Residual Fusion Network for Imbalanced Visual Regression. - Zhirong Huang; Shichao Zhang 001; Debo Cheng; Rongjiao Liang; Mengqi Jiang (APWeb-WAIM (1), 2023)

Causal Intervention for Measuring Confidence in Drug-Target Interaction Prediction. - Wenting Ye; Chen Li 027; Yang Xie; Wen Zhang 008; Hong-Yu Zhang; Bowen Wang; Debo Cheng; Zaiwen Feng (BIBM, 2023)

Disentangled Latent Representation Learning for Tackling the Confounding M-Bias Problem in Causal Inference. - Debo Cheng; Yang Xie; Ziqi Xu 001; Jiuyong Li; Lin Liu 003; Jixue Liu; Yinghao Zhang; Zaiwen Feng (ICDM, 2023)

SEM-FCNET: Semantic Feature Enhancement and Fully Convolutional Network Model for Remote Sensing Object Detection. - Jing Chen; Debo Cheng; Jiacheng Jiang; Zhongyi Yu; Shichao Zhang 001 (ICIP, 2023)

LRAGAD: Local Information Recognition for Attribute Graph Anomaly Detection. - Penghui Xi; Debo Cheng; Zhenyun Deng; Guixian Zhang; Shichao Zhang 001 (ICTAI, 2023)

MC-Net: Multi-Scale Feature Fusion and Cross-Level Information Interaction Network for Traffic Sign Detection. - Zhongyi Yu; Debo Cheng; Wenzhen Zhang; Jing Chen; Shichao Zhang 001 (ICTAI, 2023)

An Enhanced Distributed Algorithm for Area Skyline Computation Based on Apache Spark. - Chen Li 027; Yang Cao 019; Ye Zhu 002; Jinli Zhang; Annisa; Debo Cheng; Huidong Tang; Shuai Jiang; Kenta Maruyama; Yasuhiko Morimoto (KSEM (4), 2023)

A Reinforcement Learning-Based Approach for Continuous Knowledge Graph Construction. - Jiao Luo; Yitao Zhang; Ying Wang; Wolfgang Mayer; Ningpei Ding; Xiaoxia Li; Yuan Quan; Debo Cheng; Hong-Yu Zhang; Zaiwen Feng (KSEM (4), 2023)

Disentangled Representation with Causal Constraints for Counterfactual Fairness. - Ziqi Xu 001; Jixue Liu; Debo Cheng; Jiuyong Li; Lin Liu 003; Ke Wang 001 (PAKDD (1), 2023)

Learning Conditional Instrumental Variable Representation for Causal Effect Estimation. - Debo Cheng; Ziqi Xu 001; Jiuyong Li; Lin Liu 003; Thuc Duy Le; Jixue Liu (ECML/PKDD (1), 2023)

A Data-Driven Approach to Finding K for K Nearest Neighbor Matching in Average Causal Effect Estimation. - Tingting Xu; Yinghao Zhang; Jiuyong Li; Lin Liu 003; Ziqi Xu 001; Debo Cheng; Zaiwen Feng (WISE, 2023)

FastAGEDs: Fast Approximate Graph Entity Dependency Discovery. - Guangtong Zhou; Selasi Kwashie; Yidi Zhang; Michael Bewong; Vincent Mwintieru Nofong; Junwei Hu; Debo Cheng; Keqing He 002; Shanmei Liu; Zaiwen Feng (WISE, 2023)

FASTAGEDS: Fast Approximate Graph Entity Dependency Discovery. - Guangtong Zhou; Selasi Kwashie; Yidi Zhang; Michael Bewong; Vincent Mwintieru Nofong; Debo Cheng; Keqing He 002; Zaiwen Feng (CoRR, 2023)

Causal Effect Estimation with Variational AutoEncoder and the Front Door Criterion. - Ziqi Xu 001; Debo Cheng; Jiuyong Li; Jixue Liu; Lin Liu 003; Kui Yu (CoRR, 2023)

Research And Implementation Of Drug Target Interaction Confidence Measurement Method Based On Causal Intervention. - Wenting Ye; Bowen Wang; Yang Xie; Debo Cheng; Zaiwen Feng (CoRR, 2023)

Local Search for Efficient Causal Effect Estimation. - Debo Cheng; Jiuyong Li; Lin Liu 003; Jiji Zhang; Jixue Liu; Thuc Duy Le (IEEE Trans. Knowl. Data Eng., 2023)

Toward Unique and Unbiased Causal Effect Estimation From Data With Hidden Variables. - Debo Cheng; Jiuyong Li; Lin Liu 003; Kui Yu; Thuc Duy Le; Jixue Liu (IEEE Trans. Neural Networks Learn. Syst., 2023)

FPGNN: Fair path graph neural network for mitigating discrimination. - Guixian Zhang; Debo Cheng; Shichao Zhang 001 (World Wide Web (WWW), 2023)

Instrumental Variable Estimation for Causal Inference in Longitudinal Data with Time-Dependent Latent Confounders. - Debo Cheng; Ziqi Xu 001; Jiuyong Li; Lin Liu 003; Jixue Liu; Wentao Gao; Thuc Duy Le (AAAI, 2024)

Advancing Aspect-Based Sentiment Analysis Through Deep Learning Models. - Chen Li 027; Huidong Tang; Jinli Zhang; Xiujing Guo; Debo Cheng; Yasuhiko Morimoto (ADMA (5), 2024)

Multi-view Graph Neural Network for Fair Representation Learning. - Guixian Zhang; Guan Yuan; Debo Cheng; Ludan He; Rui Bing; Jiuyong Li; Shichao Zhang 001 (APWeb/WAIM (3), 2024)

TSI: A Multi-view Representation Learning Approach for Time Series Forecasting. - Wentao Gao; Ziqi Xu 001; Jiuyong Li; Lin Liu 003; Jixue Liu; Thuc Duy Le; Debo Cheng; Yanchang Zhao; Yun Chen 010 (AI (1), 2024)

A Novel Shadow Variable Catcher for Addressing Selection Bias in Recommendation Systems. - Qingfeng Chen; Boquan Wei; Debo Cheng; Jiuyong Li; Lin Liu 003; Shichao Zhang 001 (ICDM, 2024)

CaEXR: A Joint Extraction Framework for Causal Relationships Based on Word-Pair Network. - Chong Liu; Wenxiang Fang; Debo Cheng; Ruifang Zhai; Li Qin (ICIC (LNAI 4), 2024)

Conditional Instrumental Variable Regression with Representation Learning for Causal Inference. - Debo Cheng; Ziqi Xu 001; Jiuyong Li; Lin Liu 003; Jixue Liu; Thuc Duy Le (ICLR, 2024)

Causal Inference with Conditional Front-Door Adjustment and Identifiable Variational Autoencoder. - Ziqi Xu 001; Debo Cheng; Jiuyong Li; Jixue Liu; Lin Liu 003; Kui Yu (ICLR, 2024)

Enhancing the Performance of Aspect-Based Sentiment Analysis Systems. - Chen Li 027; Huidong Tang; Peng Ju; Debo Cheng; Yasuhiko Morimoto (CoRR, 2024)

Causal Effect Estimation using identifiable Variational AutoEncoder with Latent Confounders and Post-Treatment Variables. - Yang Xie; Ziqi Xu 001; Debo Cheng; Jiuyong Li; Lin Liu 003; Yinghao Zhang; Zaiwen Feng (CoRR, 2024)

Debiased Contrastive Representation Learning for Mitigating Dual Biases in Recommender Systems. - Zhirong Huang; Shichao Zhang 001; Debo Cheng; Jiuyong Li; Lin Liu 003; Guixian Zhang (CoRR, 2024)

Data-driven Conditional Instrumental Variables for Debiasing Recommender Systems. - Zhirong Huang; Shichao Zhang 001; Debo Cheng; Jiuyong Li; Lin Liu 003; Guangquan Lu (CoRR, 2024)

Estimating Peer Direct and Indirect Effects in Observational Network Data. - Xiaojing Du; Jiuyong Li; Debo Cheng; Lin Liu 003; Wentao Gao; Xiongren Chen (CoRR, 2024)

A Deconfounding Approach to Climate Model Bias Correction. - Wentao Gao; Jiuyong Li; Debo Cheng; Lin Liu 003; Jixue Liu; Thuc Duy Le; Xiaojing Du; Xiongren Chen; Yanchang Zhao; Yun Chen 010 (CoRR, 2024)

Mitigating Propensity Bias of Large Language Models for Recommender Systems. - Guixian Zhang; Guan Yuan; Debo Cheng; Lin Liu 003; Jiuyong Li; Shichao Zhang 001 (CoRR, 2024)

Towards Fair Graph Representation Learning in Social Networks. - Guixian Zhang; Guan Yuan; Debo Cheng; Lin Liu 003; Jiuyong Li; Shichao Zhang 001 (CoRR, 2024)

Multi-Cause Deconfounding for Recommender Systems with Latent Confounders. - Zhirong Huang; Shichao Zhang 001; Debo Cheng; Jiuyong Li; Lin Liu 003; Guixian Zhang (CoRR, 2024)

Mitigating Dual Latent Confounding Biases in Recommender Systems. - Jianfeng Deng; Qingfeng Chen; Debo Cheng; Jiuyong Li; Lin Liu 003; Xiaojing Du (CoRR, 2024)

Linking Model Intervention to Causal Interpretation in Model Explanation. - Debo Cheng; Ziqi Xu 001; Jiuyong Li; Lin Liu 003; Kui Yu; Thuc Duy Le; Jixue Liu (CoRR, 2024)

Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data. - Debo Cheng; Ziqi Xu 001; Jiuyong Li; Lin Liu 003; Thuc Duy Le; Xudong Guo; Shichao Zhang 001 (CoRR, 2024)

Toward Fair Graph Neural Networks Via Dual-Teacher Knowledge Distillation. - Chengyu Li; Debo Cheng; Guixian Zhang; Yi Li; Shichao Zhang 001 (CoRR, 2024)

Counterfactual Samples Constructing and Training for Commonsense Statements Estimation. - Chong Liu; Zaiwen Feng; Lin Liu 003; Zhenyun Deng; Jiuyong Li; Ruifang Zhai; Debo Cheng; Li Qin (CoRR, 2024)

Contrastive learning for fair graph representations via counterfactual graph augmentation. - Chengyu Li; Debo Cheng; Guixian Zhang; Shichao Zhang 001 (Knowl. Based Syst., 2024)

Learning fair representations via rebalancing graph structure. - Guixian Zhang; Debo Cheng; Guan Yuan; Shichao Zhang 001 (Inf. Process. Manag., 2024)

Data-Driven Causal Effect Estimation Based on Graphical Causal Modelling: A Survey. - Debo Cheng; Jiuyong Li; Lin Liu 003; Jixue Liu; Thuc Duy Le (ACM Comput. Surv., 2024)

Ripple Knowledge Graph Convolutional Networks for Recommendation Systems. - Chen Li 027; Yang Cao 019; Ye Zhu 002; Debo Cheng; Chengyuan Li; Yasuhiko Morimoto (Mach. Intell. Res., 2024)

Discovering Ancestral Instrumental Variables for Causal Inference From Observational Data. - Debo Cheng; Jiuyong Li; Lin Liu 003; Kui Yu; Thuc Duy Le; Jixue Liu (IEEE Trans. Neural Networks Learn. Syst., 2024)

Community-Centric Graph Unlearning. - Yi Li; Shichao Zhang 001; Guixian Zhang; Debo Cheng (AAAI, 2025)

Local Causal Discovery Without Causal Sufficiency. - Zhaolong Ling; Jiale Yu; Yiwen Zhang 001; Debo Cheng; Peng Zhou 006; Xingyu Wu; Bingbing Jiang 001; Kui Yu (AAAI, 2025)

Off-policy Evaluation for Multiple Actions in the Presence of Unobserved Confounders. - Haolin Wang 003; Lin Liu 003; Jiuyong Li; Ziqi Xu 001; Jixue Liu; Zehong Cao; Debo Cheng (WWW, 2025)

Mining area skyline objects from map-based big data using Apache Spark framework. - Chen Li 027; Ye Zhu 002; Yang Cao 019; Jinli Zhang; Annisa; Debo Cheng; Yasuhiko Morimoto (Array, 2025)

Certainty-aware support vector machines for fair classification. - Boyan Chen; Yuxuan Hu; Guixian Zhang; Debo Cheng; Shichao Zhang 001 (Neurocomputing, 2025)

Identifying local useful information for attribute graph anomaly detection. - Penghui Xi; Debo Cheng; Guangquan Lu; Zhenyun Deng; Guixian Zhang; Shichao Zhang 001 (Neurocomputing, 2025)

Efficient Adaptive Label Refinement for label noise learning. - Wenzhen Zhang; Debo Cheng; Guangquan Lu; Bo Zhou; Jiaye Li 001; Shichao Zhang 001 (Neurocomputing, 2025)

Leveraging long-range nodes in multi-view graph contrastive learning. - Ludan He; Debo Cheng; Guixian Zhang; Shichao Zhang 001 (Inf. Fusion, 2025)

Disentangled contrastive learning for fair graph representations. - Guixian Zhang; Guan Yuan; Debo Cheng; Lin Liu 003; Jiuyong Li; Shichao Zhang 001 (Neural Networks, 2025)

Leveraging Deep Neural Networks for Aspect-Based Sentiment Classification. - Chen Li 027; Debo Cheng; Yasuhiko Morimoto (CoRR, 2025)

A Novel Generative Model with Causality Constraint for Mitigating Biases in Recommender Systems. - Jianfeng Deng; Qingfeng Chen; Debo Cheng; Jiuyong Li; Lin Liu 003; Shichao Zhang 001 (CoRR, 2025)

Data-driven learning optimal K values for K-nearest neighbour matching in causal inference. - Yinghao Zhang; Tingting Xu; Debo Cheng; Jiuyong Li; Lin Liu 003; Ziqi Xu 001; Zaiwen Feng (Data Min. Knowl. Discov., 2025)

Deconfounding representation learning for mitigating latent confounding effects in recommendation. - Guixian Zhang; Guan Yuan; Debo Cheng; Lin Liu 003; Jiuyong Li; Ziqi Xu 001; Shichao Zhang 001 (Knowl. Inf. Syst., 2025)

Peer Effect Estimation in the Presence of Simultaneous Feedback and Unobserved Confounders. - Xiaojing Du; Jiuyong Li; Lin Liu 003; Debo Cheng; Thuc Duy Le (CoRR, 2025)

Latent Representation Learning for Attributed Graph Anomaly Detection. - Shichao Zhang 001; Penghui Xi; Mengqi Jiang; Guixian Zhang; Debo Cheng (ACM Trans. Knowl. Discov. Data, 2025)

Disentangled Representation Learning for Causal Inference With Instruments. - Debo Cheng; Jiuyong Li; Lin Liu 003; Ziqi Xu 001; Weijia Zhang 001; Jixue Liu; Thuc Duy Le (IEEE Trans. Neural Networks Learn. Syst., 2025)