A Knowledge Resources Based Neural Network for Learning Word and Relation Representations. - Shuhan Yuan; Yang Xiang 006; Maozhen Li 001 (HPCC/CSS/ICESS, 2015)

A Two Phase Deep Learning Model for Identifying Discrimination from Tweets. - Shuhan Yuan; Xintao Wu; Yang Xiang 006 (EDBT, 2016)

Incorporating Pre-Training in Long Short-Term Memory Networks for Tweets Classification. - Shuhan Yuan; Xintao Wu; Yang Xiang 006 (ICDM, 2016)

Spectrum-based Deep Neural Networks for Fraud Detection. - Shuhan Yuan; Xintao Wu; Jun Li 001; Aidong Lu (CIKM, 2017)

Differential Privacy Preserving Causal Graph Discovery. - Depeng Xu 001; Shuhan Yuan; Xintao Wu (PAC, 2017)

SNE: Signed Network Embedding. - Shuhan Yuan; Xintao Wu; Yang Xiang 006 (PAKDD (2), 2017)

Wikipedia Vandal Early Detection: From User Behavior to User Embedding. - Shuhan Yuan; Panpan Zheng; Xintao Wu; Yang Xiang 006 (ECML/PKDD (1), 2017)

FairGAN: Fairness-aware Generative Adversarial Networks. - Depeng Xu 001; Shuhan Yuan; Lu Zhang 021; Xintao Wu (IEEE BigData, 2018)

DPNE: Differentially Private Network Embedding. - Depeng Xu 001; Shuhan Yuan; Xintao Wu; NhatHai Phan (PAKDD (2), 2018)

Task-specific word identification from short texts using a convolutional neural network. - Shuhan Yuan; Xintao Wu; Yang Xiang 006 (Intell. Data Anal., 2018)

On spectral analysis of directed signed graphs. - Yuemeng Li; Shuhan Yuan; Xintao Wu; Aidong Lu (Int. J. Data Sci. Anal., 2018)

Incorporating pre-training in long short-term memory networks for tweet classification. - Shuhan Yuan; Xintao Wu; Yang Xiang 006 (Soc. Netw. Anal. Min., 2018)

One-Class Adversarial Nets for Fraud Detection. - Panpan Zheng; Shuhan Yuan; Xintao Wu; Jun Li 001; Aidong Lu (AAAI, 2019)

SAFE: A Neural Survival Analysis Model for Fraud Early Detection. - Panpan Zheng; Shuhan Yuan; Xintao Wu (AAAI, 2019)

FairGAN+: Achieving Fair Data Generation and Classification through Generative Adversarial Nets. - Depeng Xu 001; Shuhan Yuan; Lu Zhang 021; Xintao Wu (IEEE BigData, 2019)

Insider Threat Detection via Hierarchical Neural Temporal Point Processes. - Shuhan Yuan; Panpan Zheng; Xintao Wu; Qinghua Li (IEEE BigData, 2019)

Achieving Causal Fairness through Generative Adversarial Networks. - Depeng Xu 001; Yongkai Wu; Shuhan Yuan; Lu Zhang 021; Xintao Wu (IJCAI, 2019)

Dynamic Anomaly Detection Using Vector Autoregressive Model. - Yuemeng Li; Aidong Lu; Xintao Wu; Shuhan Yuan (PAKDD (1), 2019)

Achieving Differential Privacy and Fairness in Logistic Regression. - Depeng Xu 001; Shuhan Yuan; Xintao Wu (WWW (Companion Volume), 2019)

Identifying Hidden Buyers in Darknet Markets via Dirichlet Hawkes Process. - Panpan Zheng; Shuhan Yuan; Xintao Wu; Yubao Wu (CoRR, 2019)

Few-shot Insider Threat Detection. - Shuhan Yuan; Panpan Zheng; Xintao Wu; Hanghang Tong (CIKM, 2020)

InterpretableSAD: Interpretable Anomaly Detection in Sequential Log Data. - Xiao Han 008; He Cheng; Depeng Xu 001; Shuhan Yuan (IEEE BigData, 2021)

Achieving Differential Privacy in Vertically Partitioned Multiparty Learning. - Depeng Xu 001; Shuhan Yuan; Xintao Wu (IEEE BigData, 2021)

Hidden Buyer Identification in Darknet Markets via Dirichlet Hawkes Process. - Panpan Zheng; Shuhan Yuan; Xintao Wu; Yubao Wu (IEEE BigData, 2021)

Unsupervised Cross-system Log Anomaly Detection via Domain Adaptation. - Xiao Han 008; Shuhan Yuan (CIKM, 2021)

LogBERT: Log Anomaly Detection via BERT. - Haixuan Guo; Shuhan Yuan; Xintao Wu (IJCNN, 2021)

Deep learning for insider threat detection: Review, challenges and opportunities. - Shuhan Yuan; Xintao Wu (Comput. Secur., 2021)

A novel self-learning feature selection approach based on feature attributions. - Jianting Chen; Shuhan Yuan; Dongdong Lv; Yang Xiang (Expert Syst. Appl., 2021)

Sequential Anomaly Detection with Local and Global Explanations. - He Cheng; Depeng Xu 001; Shuhan Yuan (IEEE Big Data, 2022)

Fraud Detection via Contrastive Positive Unlabeled Learning. - Vinay M. S.; Shuhan Yuan; Xintao Wu (IEEE Big Data, 2022)

Contrastive Learning for Insider Threat Detection. - M. S. Vinay; Shuhan Yuan; Xintao Wu (DASFAA (1), 2022)

Generating Textual Adversaries with Minimal Perturbation. - Xingyi Zhao; Lu Zhang 021; Depeng Xu 001; Shuhan Yuan (EMNLP (Findings), 2022)

Robust Unstructured Knowledge Access in Conversational Dialogue with ASR Errors. - Yik-Cheung Tam; Jiacheng Xu; Jiakai Zou; Zecheng Wang; Tinglong Liao; Shuhan Yuan (ICASSP, 2022)

Few-shot Anomaly Detection and Classification Through Reinforced Data Selection. - Xiao Han 008; Depeng Xu 001; Shuhan Yuan; Xintao Wu (ICDM, 2022)

On the Convergence of the Monte Carlo Exploring Starts Algorithm for Reinforcement Learning. - Che Wang; Shuhan Yuan; Kai Shao; Keith W. Ross (ICLR, 2022)

Robust Hate Speech Detection via Mitigating Spurious Correlations. - Kshitiz Tiwari; Shuhan Yuan; Lu Zhang 021 (AACL/IJCNLP (2), 2022)

Coded Hate Speech Detection via Contextual Information. - Depeng Xu 001; Shuhan Yuan; Yueyang Wang; Angela Uchechukwu Nwude; Lu Zhang 021; Anna Zajicek; Xintao Wu (PAKDD (1), 2022)

Trustworthy Anomaly Detection: A Survey. - Shuhan Yuan; Xintao Wu (CoRR, 2022)

Fine-grained Anomaly Detection in Sequential Data via Counterfactual Explanations. - He Cheng; Depeng Xu 001; Shuhan Yuan; Xintao Wu (CoRR, 2022)

On Interpretable Anomaly Detection Using Causal Algorithmic Recourse. - Xiao Han 008; Lu Zhang 021; Yongkai Wu; Shuhan Yuan (CoRR, 2022)

Using Dirichlet Marked Hawkes Processes for Insider Threat Detection. - Panpan Zheng; Shuhan Yuan; Xintao Wu (DTRAP, 2022)

LogGPT: Log Anomaly Detection via GPT. - Xiao Han 008; Shuhan Yuan; Mohamed Trabelsi 003 (IEEE Big Data, 2023)

Robust Fraud Detection via Supervised Contrastive Learning. - M. S. Vinay; Shuhan Yuan; Xintao Wu (IEEE Big Data, 2023)

On Root Cause Localization and Anomaly Mitigation through Causal Inference. - Xiao Han 008; Lu Zhang 021; Yongkai Wu; Shuhan Yuan (CIKM, 2023)

Explainable Sequential Anomaly Detection via Prototypes. - He Cheng; Depeng Xu 001; Shuhan Yuan (IJCNN, 2023)

Achieving Counterfactual Fairness for Anomaly Detection. - Xiao Han 008; Lu Zhang 021; Yongkai Wu; Shuhan Yuan (PAKDD (1), 2023)

Robust Fraud Detection via Supervised Contrastive Learning. - Vinay M. S.; Shuhan Yuan; Xintao Wu (CoRR, 2023)

Algorithmic Recourse for Anomaly Detection in Multivariate Time Series. - Xiao Han 008; Lu Zhang 021; Yongkai Wu; Shuhan Yuan (CoRR, 2023)

Contrastive Learning for Fraud Detection from Noisy Labels. - Vinay M. S.; Shuhan Yuan; Xintao Wu (ICDE, 2024)

Defense against Backdoor Attack on Pre-trained Language Models via Head Pruning and Attention Normalization. - Xingyi Zhao; Depeng Xu 001; Shuhan Yuan (ICML, 2024)

Discovering and Mitigating Indirect Bias in Attention-Based Model Explanations. - Farsheed Haque; Depeng Xu 001; Shuhan Yuan (NAACL-HLT (Findings), 2024)

Backdoor Attack Against One-Class Sequential Anomaly Detection Models. - He Cheng; Shuhan Yuan (PAKDD (3), 2024)

Achieving Counterfactual Explanation for Sequence Anomaly Detection. - He Cheng; Depeng Xu 001; Shuhan Yuan; Xintao Wu (ECML/PKDD (8), 2024)

BadSAD: Clean-Label Backdoor Attacks against Deep Semi-Supervised Anomaly Detection. - He Cheng; Depeng Xu 001; Shuhan Yuan (CoRR, 2024)

Editorial: Rising stars in data mining and management 2022. - Feng Chen; Shuhan Yuan; Jilin Hu; Cheng-Te Li; Rudy Raymond; Lidan Shou (Frontiers Big Data, 2024)

Root Cause Analysis of Anomalies in Multivariate Time Series through Granger Causal Discovery. - Xiao Han; Saima Absar; Lu Zhang; Shuhan Yuan (ICLR, 2025)

Backdoor Attack against Log Anomaly Detection Models. - He Cheng; Depeng Xu 001; Shuhan Yuan (WWW (Companion Volume), 2025)