Xintao Wu - RankMe

304 papers A* 50A 13B 41C 6Misc 3Journal 126Unranked 55

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	AdaptJobRec: Enhancing Conversational Career Recommendation Through an LLM-Powered Agentic System. AAAI Qixin Wang, Dawei Wang, Kun Chen, Yaowei Hu, Puneet Girdhar, Ruoteng Wang, Aadesh Gupta, Chaitanya Devella, Wenlai Guo, Shangwen Huang, Bachir Aoun, Greg Hayworth, Han Li, Xintao Wu
2026	A*	`conf`	Class-Domain Incremental Learning on Graphs via Disentangled Knowledge Distillation. WWW Qin Tian, Chen Zhao, Xintao Wu, Dong Li, Minglai Shao, Xujiang Zhao, Wenjun Wang
2026	A*	`conf`	LLM-Enhanced Energy Contrastive Learning for Out-of-Distribution Detection in Text-Attributed Graphs. AAAI Xiaoxu Ma, Dong Li, Minglai Shao, Xintao Wu, Chen Zhao
2026	J	`jnl`	LLM-Enhanced Energy Contrastive Learning for Out-of-Distribution Detection in Text-Attributed Graphs. CoRR Xiaoxu Ma, Dong Li, Minglai Shao, Xintao Wu, Chen Zhao
2026	A*	`conf`	Out-of-Distribution Detection with Positive and Negative Prompt Supervision Using Large Language Models. AAAI Zhixia He, Chen Zhao, Minglai Shao, Xintao Wu, Xujiang Zhao, Dong Li, Qin Tian, Linlin Yu
2025	A	`conf`	A Client-level Assessment of Collaborative Backdoor Poisoning in Non-IID Federated Learning. ICDCS Phung Lai, Guanxiong Liu, NhatHai Phan, Issa Khalil, Abdallah Khreishah, Xintao Wu
2025	J	`jnl`	A Client-level Assessment of Collaborative Backdoor Poisoning in Non-IID Federated Learning. CoRR Phung Lai, Guanxiong Liu, NhatHai Phan, Issa Khalil, Abdallah Khreishah, Xintao Wu
2025	B	`conf`	A Hybrid Large Vision Model Powered GUI Agent for Walmart Myassistant Application. IEEE Big Data Qixin Wang, Puneet Girdhar, Yaowei Hu, Dawei Wang, Yifan Wang, Chaitanya Devella, Ayush Dwivedi, Wenlai Guo, Terrence Liu, Manmohan Dogra, Kun Chen, Yu Zheng, Shangwen Huang, Swati Pandey, Balram Mirani, Diwash Pokharel, Greg Hayworth, Han Li, Xintao Wu
2025	B	`conf`	A Machine Learning Framework for Automated Computational Ethology Using Markerless Pose Estimation. IEEE Big Data Prateek Verma, Minh-Hao Van, Christopher McEnaney, Ashtyn Le, Amy R. Poe, Xintao Wu
2025	J	`jnl`	A Survey of AI for Materials Science: Foundation Models, LLM Agents, Datasets, and Tools. CoRR Minh-Hao Van, Prateek Verma, Chen Zhao, Xintao Wu
2025	J	`jnl`	A Survey on Computational Pathology Foundation Models: Datasets, Adaptation Strategies, and Evaluation Tasks. CoRR Dong Li, Guihong Wan, Xintao Wu, Xinyu Wu, Ajit Johnson Nirmal, Christine G. Lian, Peter K. Sorger, Yevgeniy R. Semenov, Chen Zhao
2025	J	`jnl`	Achieving Distributive Justice in Federated Learning via Uncertainty Quantification. CoRR Alycia N. Carey, Xintao Wu
2025	—	`conf`	Achieving Flexible Local Differential Privacy in Federated Learning via Influence Functions. ECML/PKDD (5) Alycia N. Carey, Xintao Wu
2025	J	`jnl`	AdaptJobRec: Enhancing Conversational Career Recommendation through an LLM-Powered Agentic System. CoRR Qixin Wang, Dawei Wang, Kun Chen, Yaowei Hu, Puneet Girdhar, Ruoteng Wang, Aadesh Gupta, Chaitanya Devella, Wenlai Guo, Shangwen Huang, Bachir Aoun, Greg Hayworth, Han Li, Xintao Wu
2025	—	`ed.`	Advances in Knowledge Discovery and Data Mining - 29th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2025, Sydney, NSW, Australia, June 10-13, 2025, Proceedings, Part I PAKDD (1) Xintao Wu, Myra Spiliopoulou, Can Wang, Vipin Kumar, Longbing Cao, Yanqiu Wu, Yu Yao, Zhangkai Wu
2025	—	`ed.`	Advances in Knowledge Discovery and Data Mining - 29th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2025, Sydney, NSW, Australia, June 10-13, 2025, Proceedings, Part II PAKDD (2) Xintao Wu, Myra Spiliopoulou, Can Wang, Vipin Kumar, Longbing Cao, Yanqiu Wu, Yu Yao, Zhangkai Wu
2025	—	`ed.`	Advances in Knowledge Discovery and Data Mining - 29th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2025, Sydney, NSW, Australia, June 10-13, 2025, Proceedings, Part III PAKDD (3) Xintao Wu, Myra Spiliopoulou, Can Wang, Vipin Kumar, Longbing Cao, Yanqiu Wu, Yu Yao, Zhangkai Wu
2025	—	`ed.`	Advances in Knowledge Discovery and Data Mining - 29th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2025, Sydney, NSW, Australia, June 10-13, 2025, Proceedings, Part IV PAKDD (4) Xintao Wu, Myra Spiliopoulou, Can Wang, Vipin Kumar, Longbing Cao, Yanqiu Wu, Yu Yao, Zhangkai Wu
2025	—	`ed.`	Advances in Knowledge Discovery and Data Mining - 29th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2025, Sydney, NSW, Australia, June 10-13, 2025, Proceedings, Part V PAKDD (5) Xintao Wu, Myra Spiliopoulou, Can Wang, Vipin Kumar, Longbing Cao, Yanqiu Wu, Yu Yao, Zhangkai Wu
2025	A*	`conf`	CausalVLBench: Benchmarking Visual Causal Reasoning in Large Vision-Language Models. EMNLP Aneesh Komanduri, Karuna Bhaila, Xintao Wu
2025	J	`jnl`	CausalVLBench: Benchmarking Visual Causal Reasoning in Large Vision-Language Models. CoRR Aneesh Komanduri, Karuna Bhaila, Xintao Wu
2025	J	`jnl`	Cross-Modal Attention Guided Unlearning in Vision-Language Models. CoRR Karuna Bhaila, Aneesh Komanduri, Minh-Hao Van, Xintao Wu
2025	—	`ed.`	Data Science: Foundations and Applications - 29th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2025, Sydney, Australia, June 10-13, 2025, Proceedings, Part VII PAKDD (7) Xintao Wu, Myra Spiliopoulou, Can Wang, Vipin Kumar, Longbing Cao, Xiangmin Zhou, Guansong Pang, João Gama
2025	—	`ed.`	Data Science: Foundations and Applications - 29th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2025, Sydney, NSW, Australia, June 10-13, 2025, Proceedings, Part VI PAKDD (6) Xintao Wu, Myra Spiliopoulou, Can Wang, Vipin Kumar, Longbing Cao, Xiangmin Zhou, Guansong Pang, João Gama
2025	J	`jnl`	Detecting and Mitigating Hateful Content in Multimodal Memes with Vision-Language Models. CoRR Minh-Hao Van, Xintao Wu
2025	J	`jnl`	Face4FairShifts: A Large Image Benchmark for Fairness and Robust Learning across Visual Domains. CoRR Yumeng Lin, Dong Li, Xintao Wu, Minglai Shao, Xujiang Zhao, Zhong Chen, Chen Zhao
2025	B	`conf`	Fair In-Context Learning via Latent Concept Variables. IEEE Big Data Karuna Bhaila, Minh-Hao Van, Kennedy Edemacu, Chen Zhao, Feng Chen, Xintao Wu
2025	A*	`conf`	Fairness-Aware Active Online Learning with Changing Environments. ICDE Sadaf Md. Halim, Chen Zhao, Xintao Wu, Latifur Khan, Christan Earl Grant, Feng Chen
2025	J	`jnl`	Few-shot anomaly detection and classification through reinforced data selection with a combinatorial reward. Knowl. Inf. Syst. Xiao Han, Depeng Xu, Shuhan Yuan, Xintao Wu
2025	B	`conf`	Fine-Tuning Vision-Language Models for Multimodal Polymer Property Prediction. IEEE Big Data An Vuong, Minh-Hao Van, Prateek Verma, Chen Zhao, Xintao Wu
2025	J	`jnl`	Fine-Tuning Vision-Language Models for Multimodal Polymer Property Prediction. CoRR An Vuong, Minh-Hao Van, Prateek Verma, Chen Zhao, Xintao Wu
2025	J	`jnl`	Influence-based approaches for tumor classification in noisy brain MRI with deep learning and vision-language models. Int. J. Data Sci. Anal. Minh-Hao Van, Alycia N. Carey, Xintao Wu
2025	—	`conf`	Let The Jury Decide: Fair Demonstration Selection for In-Context Learning through Incremental Greedy Evaluation. ACL (Findings) Sadaf Md. Halim, Chen Zhao, Xintao Wu, Latifur Khan, Christan Grant, Fariha Ishrat Rahman, Feng Chen
2025	J	`jnl`	Multi-Modal Foundation Models for Computational Pathology: A Survey. CoRR Dong Li, Guihong Wan, Xintao Wu, Xinyu Wu, Xiaohui Chen, Yi He, Christine G. Lian, Peter K. Sorger, Yevgeniy R. Semenov, Chen Zhao
2025	J	`jnl`	Multi-Modal Foundation Models for Computational Pathology: A Survey. Trans. Mach. Learn. Res. Dong Li, Guihong Wan, Xintao Wu, Xinyu Wu, Xiaohui Chen, Yi He, Zhong Chen, Peter K. Sorger, Chen Zhao
2025	J	`jnl`	Out-of-Distribution Detection with Positive and Negative Prompt Supervision Using Large Language Models. CoRR Zhixia He, Chen Zhao, Minglai Shao, Xintao Wu, Xujiang Zhao, Dong Li, Qin Tian, Linlin Yu
2025	J	`jnl`	Privacy Preserving Prompt Engineering: A Survey. ACM Comput. Surv. Kennedy Edemacu, Xintao Wu
2025	—	`conf`	Soft Prompting for Unlearning in Large Language Models. NAACL (Long Papers) Karuna Bhaila, Minh-Hao Van, Xintao Wu
2025	—	`conf`	The 4th Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI). KDD (2) Chen Zhao, Feng Chen, Xintao Wu, Haifeng Chen
2024	A*	`conf`	3rd Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI). KDD Chen Zhao, Feng Chen, Xintao Wu, Jundong Li, Haifeng Chen
2024	—	`conf`	Achieving Counterfactual Explanation for Sequence Anomaly Detection. ECML/PKDD (8) He Cheng, Depeng Xu, Shuhan Yuan, Xintao Wu
2024	A*	`conf`	Algorithmic Fairness Generalization under Covariate and Dependence Shifts Simultaneously. KDD Chen Zhao, Kai Jiang, Xintao Wu, Haoliang Wang, Latifur Khan, Christan Grant, Feng Chen
2024	B	`conf`	Beyond Human Vision: The Role of Large Vision Language Models in Microscope Image Analysis. IEEE Big Data Prateek Verma, Minh-Hao Van, Xintao Wu
2024	J	`jnl`	Beyond Human Vision: The Role of Large Vision Language Models in Microscope Image Analysis. CoRR Prateek Verma, Minh-Hao Van, Xintao Wu
2024	B	`conf`	Cascading Failure Prediction in Power Grid Using Node and Edge Attributed Graph Neural Networks. IJCNN Karuna Bhaila, Xintao Wu
2024	A	`conf`	Causal Diffusion Autoencoders: Toward Counterfactual Generation via Diffusion Probabilistic Models. ECAI Aneesh Komanduri, Chen Zhao, Feng Chen, Xintao Wu
2024	J	`jnl`	Causal Diffusion Autoencoders: Toward Counterfactual Generation via Diffusion Probabilistic Models. CoRR Aneesh Komanduri, Chen Zhao, Feng Chen, Xintao Wu
2024	B	`conf`	Content-Aware Deep Learning Recommender System. IEEE Big Data Qixin Wang, Xintao Wu, Kan Yao, Han Li
2024	A*	`conf`	Contrastive Learning for Fraud Detection from Noisy Labels. ICDE Vinay M. S., Shuhan Yuan, Xintao Wu
2024	B	`conf`	DP-TabICL: In-Context Learning with Differentially Private Tabular Data. IEEE Big Data Alycia N. Carey, Karuna Bhaila, Kennedy Edemacu, Xintao Wu
2024	J	`jnl`	DP-TabICL: In-Context Learning with Differentially Private Tabular Data. CoRR Alycia N. Carey, Karuna Bhaila, Kennedy Edemacu, Xintao Wu
2024	J	`jnl`	Dynamic Environment Responsive Online Meta-Learning with Fairness Awareness. CoRR Chen Zhao, Feng Mi, Xintao Wu, Kai Jiang, Latifur Khan, Feng Chen
2024	J	`jnl`	Dynamic Environment Responsive Online Meta-Learning with Fairness Awareness. ACM Trans. Knowl. Discov. Data Chen Zhao, Feng Mi, Xintao Wu, Kai Jiang, Latifur Khan, Feng Chen
2024	B	`conf`	Evaluating the Impact of Local Differential Privacy on Utility Loss via Influence Functions. IJCNN Alycia N. Carey, Minh-Hao Van, Xintao Wu
2024	J	`jnl`	Fair In-Context Learning via Latent Concept Variables. CoRR Karuna Bhaila, Minh-Hao Van, Kennedy Edemacu, Chen Zhao, Feng Chen, Xintao Wu
2024	B	`conf`	Federated Learning under Sample Selection Heterogeneity. IEEE Big Data Huy Mai, Xintao Wu
2024	J	`jnl`	From Identifiable Causal Representations to Controllable Counterfactual Generation: A Survey on Causal Generative Modeling. Trans. Mach. Learn. Res. Aneesh Komanduri, Xintao Wu, Yongkai Wu, Feng Chen
2024	J	`jnl`	In-Context Learning Demonstration Selection via Influence Analysis. CoRR Vinay M. S., Minh-Hao Van, Xintao Wu
2024	C	`ed.`	International Conference on Machine Learning and Applications, ICMLA 2024, Miami, FL, USA, December 18-20, 2024 ICMLA M. Arif Wani, Plamen Angelov, Feng Luo, Mitsunori Ogihara, Xintao Wu, Radu-Emil Precup, Ramin Ramezani, Xiaowei Gu
2024	A*	`conf`	Learning Causally Disentangled Representations via the Principle of Independent Causal Mechanisms. IJCAI Aneesh Komanduri, Yongkai Wu, Feng Chen, Xintao Wu
2024	A	`conf`	Local Differential Privacy in Graph Neural Networks: a Reconstruction Approach. SDM Karuna Bhaila, Wen Huang, Yongkai Wu, Xintao Wu
2024	B	`conf`	On Large Visual Language Models for Medical Imaging Analysis: An Empirical Study. CHASE Minh-Hao Van, Prateek Verma, Xintao Wu
2024	J	`jnl`	On Large Visual Language Models for Medical Imaging Analysis: An Empirical Study. CoRR Minh-Hao Van, Prateek Verma, Xintao Wu
2024	B	`conf`	On Prediction Feature Assignment in the Heckman Selection Model. IJCNN Huy Mai, Xintao Wu
2024	J	`jnl`	Privacy Preserving Prompt Engineering: A Survey. CoRR Kennedy Edemacu, Xintao Wu
2024	—	`conf`	Robust Influence-Based Training Methods for Noisy Brain MRI. PKDD (4) Minh-Hao Van, Alycia N. Carey, Xintao Wu
2024	J	`jnl`	Robust Influence-based Training Methods for Noisy Brain MRI. CoRR Minh-Hao Van, Alycia N. Carey, Xintao Wu
2024	A*	`conf`	Robustly Improving Bandit Algorithms with Confounded and Selection Biased Offline Data: A Causal Approach. AAAI Wen Huang, Xintao Wu
2024	J	`jnl`	Soft Prompting for Unlearning in Large Language Models. CoRR Karuna Bhaila, Minh-Hao Van, Xintao Wu
2024	A*	`conf`	Supervised Algorithmic Fairness in Distribution Shifts: A Survey. IJCAI Minglai Shao, Dong Li, Chen Zhao, Xintao Wu, Yujie Lin, Qin Tian
2024	J	`jnl`	Supervised Algorithmic Fairness in Distribution Shifts: A Survey. CoRR Yujie Lin, Dong Li, Chen Zhao, Xintao Wu, Qin Tian, Minglai Shao
2024	J	`jnl`	WSA-YOLOv5s: improved YOLOv5s based on window self-attention module for ship detection. Pattern Anal. Appl. Weina Zhou, Hong Wang, Xintao Wu
2023	A*	`conf`	2nd Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI). KDD Chen Zhao, Feng Chen, Xintao Wu, Haifeng Chen, Jiayu Zhou
2023	J	`jnl`	A Robust Classifier Under Missing-Not-At-Random Sample Selection Bias. CoRR Huy Mai, Wen Huang, Wei Du, Xintao Wu
2023	B	`conf`	A Robust Classifier under Missing-Not-at-Random Sample Selection Bias. IEEE Big Data Huy Mai, Wen Huang, Wei Du, Xintao Wu
2023	J	`jnl`	Detecting and Correcting Hate Speech in Multimodal Memes with Large Visual Language Model. CoRR Minh-Hao Van, Xintao Wu
2023	J	`jnl`	Evaluating the Impact of Local Differential Privacy on Utility Loss via Influence Functions. CoRR Alycia N. Carey, Minh-Hao Van, Xintao Wu
2023	J	`jnl`	Fairness-Aware Domain Generalization under Covariate and Dependence Shifts. CoRR Chen Zhao, Kai Jiang, Xintao Wu, Haoliang Wang, Latifur Khan, Christan Grant, Feng Chen
2023	J	`jnl`	From Identifiable Causal Representations to Controllable Counterfactual Generation: A Survey on Causal Generative Modeling. CoRR Aneesh Komanduri, Xintao Wu, Yongkai Wu, Feng Chen
2023	A*	`conf`	HINT: Healthy Influential-Noise based Training to Defend against Data Poisoning Attacks. ICDM Minh-Hao Van, Alycia N. Carey, Xintao Wu
2023	J	`jnl`	HINT: Healthy Influential-Noise based Training to Defend against Data Poisoning Attacks. CoRR Minh-Hao Van, Alycia N. Carey, Xintao Wu
2023	B	`conf`	Investigating the Impact of Skill-Related Videos on Online Learning. L@S Ethan Prihar, Aaron Haim, Tracy Jia Shen, Adam Sales, Dongwon Lee, Xintao Wu, Neil T. Heffernan
2023	J	`jnl`	Learning Causally Disentangled Representations via the Principle of Independent Causal Mechanisms. CoRR Aneesh Komanduri, Yongkai Wu, Feng Chen, Xintao Wu
2023	J	`jnl`	Local Differential Privacy in Graph Neural Networks: a Reconstruction Approach. CoRR Karuna Bhaila, Wen Huang, Yongkai Wu, Xintao Wu
2023	B	`conf`	Mitigating Confounding and Selection Biases in Personalized Recommendation: A Causal Approach. IEEE Big Data Wen Huang, Jingbo Zhou, Xintao Wu, Dejing Dou
2023	J	`jnl`	On Prediction Feature Assignment in the Heckman Selection Model. CoRR Huy Mai, Xintao Wu
2023	B	`conf`	Randomized Response Has No Disparate Impact on Model Accuracy. IEEE Big Data Alycia N. Carey, Karuna Bhaila, Xintao Wu
2023	B	`conf`	Robust Fraud Detection via Supervised Contrastive Learning. IEEE Big Data M. S. Vinay, Shuhan Yuan, Xintao Wu
2023	J	`jnl`	Robust Fraud Detection via Supervised Contrastive Learning. CoRR Vinay M. S., Shuhan Yuan, Xintao Wu
2023	J	`jnl`	Robustly Improving Bandit Algorithms with Confounded and Selection Biased Offline Data: A Causal Approach. CoRR Wen Huang, Xintao Wu
2023	J	`jnl`	The statistical fairness field guide: perspectives from social and formal sciences. AI Ethics Alycia N. Carey, Xintao Wu
2023	A*	`conf`	Towards Fair Disentangled Online Learning for Changing Environments. KDD Chen Zhao, Feng Mi, Xintao Wu, Kai Jiang, Latifur Khan, Christan Grant, Feng Chen
2023	J	`jnl`	Towards Fair Disentangled Online Learning for Changing Environments. CoRR Chen Zhao, Feng Mi, Xintao Wu, Kai Jiang, Latifur Khan, Christan Grant, Feng Chen
2022	A*	`conf`	1st ACM SIGKDD Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI-KDD22). KDD Chen Zhao, Feng Chen, Xintao Wu, Christopher Funk, Anthony Hoogs
2022	A*	`conf`	Achieving Counterfactual Fairness for Causal Bandit. AAAI Wen Huang, Lu Zhang, Xintao Wu
2022	J	`jnl`	Achieving User-Side Fairness in Contextual Bandits. Hum. Centric Intell. Syst. Wen Huang, Kevin Labille, Xintao Wu, Dongwon Lee, Neil T. Heffernan
2022	A*	`conf`	Adaptive Fairness-Aware Online Meta-Learning for Changing Environments. KDD Chen Zhao, Feng Mi, Xintao Wu, Kai Jiang, Latifur Khan, Feng Chen
2022	J	`jnl`	Adaptive Fairness-Aware Online Meta-Learning for Changing Environments. CoRR Chen Zhao, Feng Mi, Xintao Wu, Kai Jiang, Latifur Khan, Feng Chen
2022	—	`conf`	Coded Hate Speech Detection via Contextual Information. PAKDD (1) Depeng Xu, Shuhan Yuan, Yueyang Wang, Angela Uchechukwu Nwude, Lu Zhang, Anna Zajicek, Xintao Wu
2022	—	`conf`	Contrastive Learning for Insider Threat Detection. DASFAA (1) M. S. Vinay, Shuhan Yuan, Xintao Wu
2022	B	`conf`	Defending Evasion Attacks via Adversarially Adaptive Training. IEEE Big Data Minh-Hao Van, Wei Du, Xintao Wu, Feng Chen, Aidong Lu
2022	B	`conf`	Fair Collective Classification in Networked Data. IEEE Big Data Karuna Bhaila, Yongkai Wu, Xintao Wu
2022	B	`conf`	Fair Regression under Sample Selection Bias. IEEE Big Data Wei Du, Xintao Wu, Hanghang Tong
2022	A*	`conf`	Few-shot Anomaly Detection and Classification Through Reinforced Data Selection. ICDM Xiao Han, Depeng Xu, Shuhan Yuan, Xintao Wu
2022	J	`jnl`	Fine-grained Anomaly Detection in Sequential Data via Counterfactual Explanations. CoRR He Cheng, Depeng Xu, Shuhan Yuan, Xintao Wu
2022	B	`conf`	Fraud Detection via Contrastive Positive Unlabeled Learning. IEEE Big Data Vinay M. S., Shuhan Yuan, Xintao Wu
2022	B	`conf`	Heterogeneous Randomized Response for Differential Privacy in Graph Neural Networks. IEEE Big Data Khang Tran, Phung Lai, NhatHai Phan, Issa Khalil, Yao Ma, Abdallah Khreishah, My T. Thai, Xintao Wu
2022	J	`jnl`	Heterogeneous Randomized Response for Differential Privacy in Graph Neural Networks. CoRR Khang Tran, Phung Lai, NhatHai Phan, Issa Khalil, Yao Ma, Abdallah Khreishah, My Tra Thai, Xintao Wu
2022	B	`conf`	InfoFair: Information-Theoretic Intersectional Fairness. IEEE Big Data Jian Kang, Tiankai Xie, Xintao Wu, Ross Maciejewski, Hanghang Tong
2022	J	`jnl`	Model Transferring Attacks to Backdoor HyperNetwork in Personalized Federated Learning. CoRR Phung Lai, NhatHai Phan, Abdallah Khreishah, Issa Khalil, Xintao Wu
2022	J	`jnl`	Modeling and reliability verification of industrial control network protocol based on time state transition matrix. Int. J. Commun. Syst. Jie Wang, Xintao Wu, Gang Hou, Pengfei Li, Ao Gao, Zhichao Chen, Haoyu Gao
2022	—	`conf`	Poisoning Attacks on Fair Machine Learning. DASFAA (1) Minh-Hao Van, Wei Du, Xintao Wu, Aidong Lu
2022	B	`conf`	Robust Personalized Federated Learning under Demographic Fairness Heterogeneity. IEEE Big Data Alycia N. Carey, Wei Du, Xintao Wu
2022	B	`conf`	SCM-VAE: Learning Identifiable Causal Representations via Structural Knowledge. IEEE Big Data Aneesh Komanduri, Yongkai Wu, Wen Huang, Feng Chen, Xintao Wu
2022	J	`jnl`	The Causal Fairness Field Guide: Perspectives From Social and Formal Sciences. Frontiers Big Data Alycia N. Carey, Xintao Wu
2022	J	`jnl`	The Fairness Field Guide: Perspectives from Social and Formal Sciences. CoRR Alycia N. Carey, Xintao Wu
2022	J	`jnl`	Trustworthy Anomaly Detection: A Survey. CoRR Shuhan Yuan, Xintao Wu
2022	J	`jnl`	Using Dirichlet Marked Hawkes Processes for Insider Threat Detection. DTRAP Panpan Zheng, Shuhan Yuan, Xintao Wu
2021	A*	`conf`	A Generative Adversarial Framework for Bounding Confounded Causal Effects. AAAI Yaowei Hu, Yongkai Wu, Lu Zhang, Xintao Wu
2021	—	`conf`	A Modeling and Verification Method of Modbus TCP/IP Protocol. ICA3PP (3) Jie Wang, Zhichao Chen, Gang Hou, Haoyu Gao, Pengfei Li, Ao Gao, Xintao Wu
2021	J	`jnl`	Achieving Counterfactual Fairness for Causal Bandit. CoRR Wen Huang, Lu Zhang, Xintao Wu
2021	—	`conf`	Achieving Differential Privacy in Vertically Partitioned Multiparty Learning. IEEE BigData Depeng Xu, Shuhan Yuan, Xintao Wu
2021	A*	`conf`	Attent: Active Attributed Network Alignment. WWW Qinghai Zhou, Liangyue Li, Xintao Wu, Nan Cao, Lei Ying, Hanghang Tong
2021	J	`jnl`	Classifying Math KCs via Task-Adaptive Pre-Trained BERT. CoRR Jia Tracy Shen, Michiharu Yamashita, Ethan Prihar, Neil T. Heffernan, Xintao Wu, Sean McGrew, Dongwon Lee
2021	—	`conf`	Classifying Math Knowledge Components via Task-Adaptive Pre-Trained BERT. AIED (1) Jia Tracy Shen, Michiharu Yamashita, Ethan Prihar, Neil T. Heffernan, Xintao Wu, Sean McGrew, Dongwon Lee
2021	J	`jnl`	Deep learning for insider threat detection: Review, challenges and opportunities. Comput. Secur. Shuhan Yuan, Xintao Wu
2021	J	`jnl`	Enhancing personalized modeling via weighted and adversarial learning. Int. J. Data Sci. Anal. Wei Du, Xintao Wu
2021	J	`jnl`	Fair Regression under Sample Selection Bias. CoRR Wei Du, Xintao Wu, Hanghang Tong
2021	A	`conf`	Fair and Robust Classification Under Sample Selection Bias. CIKM Wei Du, Xintao Wu
2021	A	`conf`	Fairness-aware Agnostic Federated Learning. SDM Wei Du, Depeng Xu, Xintao Wu, Hanghang Tong
2021	—	`conf`	Fairness-aware Bandit-based Recommendation. IEEE BigData Wen Huang, Kevin Labille, Xintao Wu, Dongwon Lee, Neil T. Heffernan
2021	—	`conf`	Hidden Buyer Identification in Darknet Markets via Dirichlet Hawkes Process. IEEE BigData Panpan Zheng, Shuhan Yuan, Xintao Wu, Yubao Wu
2021	B	`conf`	LogBERT: Log Anomaly Detection via BERT. IJCNN Haixuan Guo, Shuhan Yuan, Xintao Wu
2021	J	`jnl`	LogBERT: Log Anomaly Detection via BERT. CoRR Haixuan Guo, Shuhan Yuan, Xintao Wu
2021	—	`conf`	Managing Uncertainty in Crowdsourcing with Interval-Valued Labels. NAFIPS Chenyi Hu, Victor S. Sheng, Ningning Wu, Xintao Wu
2021	J	`jnl`	MathBERT: A Pre-trained Language Model for General NLP Tasks in Mathematics Education. CoRR Jia Tracy Shen, Michiharu Yamashita, Ethan Prihar, Neil T. Heffernan, Xintao Wu, Dongwon Lee
2021	J	`jnl`	MultiFair: Multi-Group Fairness in Machine Learning. CoRR Jian Kang, Tiankai Xie, Xintao Wu, Ross Maciejewski, Hanghang Tong
2021	J	`jnl`	Poisoning Attacks on Fair Machine Learning. CoRR Minh-Hao Van, Wei Du, Xintao Wu, Aidong Lu
2021	A*	`conf`	Removing Disparate Impact on Model Accuracy in Differentially Private Stochastic Gradient Descent. KDD Depeng Xu, Wei Du, Xintao Wu
2021	J	`jnl`	Robust Fairness-aware Learning Under Sample Selection Bias. CoRR Wei Du, Xintao Wu
2021	J	`jnl`	Towards Learning-Based, Content-Agnostic Detection of Social Bot Traffic. IEEE Trans. Dependable Secur. Comput. Yebo Feng, Jun Li, Lei Jiao, Xintao Wu
2021	—	`conf`	Transferable Contextual Bandits with Prior Observations. PAKDD (2) Kevin Labille, Wen Huang, Xintao Wu
2021	J	`jnl`	oGBAC - A Group Based Access Control Framework for Information Sharing in Online Social Networks. IEEE Trans. Dependable Secur. Comput. Donghui Hu, Chunya Hu, Yuqi Fan, Xintao Wu
2020	—	`ed.`	2020 IEEE International Conference on Big Data (IEEE BigData 2020), Atlanta, GA, USA, December 10-13, 2020 IEEE BigData Xintao Wu, Chris Jermaine, Li Xiong, Xiaohua Hu, Olivera Kotevska, Siyuan Lu, Weija Xu, Srinivas Aluru, ChengXiang Zhai, Eyhab Al-Masri, Zhiyuan Chen, Jeff Saltz
2020	J	`jnl`	Achieving User-Side Fairness in Contextual Bandits. CoRR Wen Huang, Kevin Labille, Xintao Wu, Dongwon Lee, Neil T. Heffernan
2020	B	`conf`	AdvPL: Adversarial Personalized Learning. DSAA Wei Du, Xintao Wu
2020	A	`conf`	Database-Access Performance Antipatterns in Database-Backed Web Applications. ICSME Shudi Shao, Zhengyi Qiu, Xiao Yu, Wei Yang, Guoliang Jin, Tao Xie, Xintao Wu
2020	J	`jnl`	Deep Learning for Insider Threat Detection: Review, Challenges and Opportunities. CoRR Shuhan Yuan, Xintao Wu
2020	A*	`conf`	Fair Multiple Decision Making Through Soft Interventions. NeurIPS Yaowei Hu, Yongkai Wu, Lu Zhang, Xintao Wu
2020	—	`conf`	Fairness through Equality of Effort. WWW (Companion Volume) Wen Huang, Yongkai Wu, Lu Zhang, Xintao Wu
2020	J	`jnl`	Fairness-aware Agnostic Federated Learning. CoRR Wei Du, Depeng Xu, Xintao Wu, Hanghang Tong
2020	A	`conf`	Few-shot Insider Threat Detection. CIKM Shuhan Yuan, Panpan Zheng, Xintao Wu, Hanghang Tong
2020	—	`conf`	Multi-cause Discrimination Analysis Using Potential Outcomes. SBP-BRiMS Wen Huang, Yongkai Wu, Xintao Wu
2020	J	`jnl`	Removing Disparate Impact of Differentially Private Stochastic Gradient Descent on Model Accuracy. CoRR Depeng Xu, Wei Du, Xintao Wu
2019	A*	`conf`	Achieving Causal Fairness through Generative Adversarial Networks. IJCAI Depeng Xu, Yongkai Wu, Shuhan Yuan, Lu Zhang, Xintao Wu
2019	—	`conf`	Achieving Differential Privacy and Fairness in Logistic Regression. WWW (Companion Volume) Depeng Xu, Shuhan Yuan, Xintao Wu
2019	J	`jnl`	Achieving Differential Privacy in Vertically Partitioned Multiparty Learning. CoRR Depeng Xu, Shuhan Yuan, Xintao Wu
2019	J	`jnl`	Bayesian Network Construction and Genotype-Phenotype Inference Using GWAS Statistics. IEEE ACM Trans. Comput. Biol. Bioinform. Lu Zhang, Qiuping Pan, Yue Wang, Xintao Wu, Xinghua Shi
2019	—	`conf`	BotFlowMon: Learning-based, Content-Agnostic Identification of Social Bot Traffic Flows. CNS Yebo Feng, Jun Li, Lei Jiao, Xintao Wu
2019	J	`jnl`	Causal Modeling-Based Discrimination Discovery and Removal: Criteria, Bounds, and Algorithms. IEEE Trans. Knowl. Data Eng. Lu Zhang, Yongkai Wu, Xintao Wu
2019	—	`conf`	Characteristics of Bitcoin Transactions on Cryptomarkets. SpaCCS Xucan Chen, Mohammad Al Hasan, Xintao Wu, Pavel Skums, Mohammad Javad Feizollahi, Marie Ouellet, Eric L. Sevigny, David Maimon, Yubao Wu
2019	A*	`conf`	Counterfactual Fairness: Unidentification, Bound and Algorithm. IJCAI Yongkai Wu, Lu Zhang, Xintao Wu
2019	—	`conf`	Dynamic Anomaly Detection Using Vector Autoregressive Model. PAKDD (1) Yuemeng Li, Aidong Lu, Xintao Wu, Shuhan Yuan
2019	—	`conf`	FairGAN IEEE BigData Depeng Xu, Shuhan Yuan, Lu Zhang, Xintao Wu
2019	J	`jnl`	Fairness through Equality of Effort. CoRR Wen Huang, Yongkai Wu, Lu Zhang, Xintao Wu
2019	A*	`conf`	Heterogeneous Gaussian Mechanism: Preserving Differential Privacy in Deep Learning with Provable Robustness. IJCAI NhatHai Phan, Minh N. Vu, Yang Liu, Ruoming Jin, Dejing Dou, Xintao Wu, My T. Thai
2019	J	`jnl`	Heterogeneous Gaussian Mechanism: Preserving Differential Privacy in Deep Learning with Provable Robustness. CoRR NhatHai Phan, Minh N. Vu, Yang Liu, Ruoming Jin, Dejing Dou, Xintao Wu, My T. Thai
2019	J	`jnl`	Identifying Hidden Buyers in Darknet Markets via Dirichlet Hawkes Process. CoRR Panpan Zheng, Shuhan Yuan, Xintao Wu, Yubao Wu
2019	—	`conf`	Insider Threat Detection via Hierarchical Neural Temporal Point Processes. IEEE BigData Shuhan Yuan, Panpan Zheng, Xintao Wu, Qinghua Li
2019	J	`jnl`	Insider Threat Detection via Hierarchical Neural Temporal Point Processes. CoRR Shuhan Yuan, Panpan Zheng, Xintao Wu, Qinghua Li
2019	A*	`conf`	On Convexity and Bounds of Fairness-aware Classification. WWW Yongkai Wu, Lu Zhang, Xintao Wu
2019	A*	`conf`	One-Class Adversarial Nets for Fraud Detection. AAAI Panpan Zheng, Shuhan Yuan, Xintao Wu, Jun Li, Aidong Lu
2019	A*	`conf`	PC-Fairness: A Unified Framework for Measuring Causality-based Fairness. NeurIPS Yongkai Wu, Lu Zhang, Xintao Wu, Hanghang Tong
2019	J	`jnl`	PC-Fairness: A Unified Framework for Measuring Causality-based Fairness. CoRR Yongkai Wu, Lu Zhang, Xintao Wu, Hanghang Tong
2019	A*	`conf`	SAFE: A Neural Survival Analysis Model for Fraud Early Detection. AAAI Panpan Zheng, Shuhan Yuan, Xintao Wu
2018	A*	`conf`	Achieving Non-Discrimination in Prediction. IJCAI Lu Zhang, Yongkai Wu, Xintao Wu
2018	—	`conf`	DPNE: Differentially Private Network Embedding. PAKDD (2) Depeng Xu, Shuhan Yuan, Xintao Wu, NhatHai Phan
2018	—	`conf`	FairGAN: Fairness-aware Generative Adversarial Networks. IEEE BigData Depeng Xu, Shuhan Yuan, Lu Zhang, Xintao Wu
2018	J	`jnl`	FairGAN: Fairness-aware Generative Adversarial Networks. CoRR Depeng Xu, Shuhan Yuan, Lu Zhang, Xintao Wu
2018	J	`jnl`	Fairness-aware Classification: Criterion, Convexity, and Bounds. CoRR Yongkai Wu, Lu Zhang, Xintao Wu
2018	J	`jnl`	Incorporating pre-training in long short-term memory networks for tweet classification. Soc. Netw. Anal. Min. Shuhan Yuan, Xintao Wu, Yang Xiang
2018	A*	`conf`	On Discrimination Discovery and Removal in Ranked Data using Causal Graph. KDD Yongkai Wu, Lu Zhang, Xintao Wu
2018	J	`jnl`	On Discrimination Discovery and Removal in Ranked Data using Causal Graph. CoRR Yongkai Wu, Lu Zhang, Xintao Wu
2018	J	`jnl`	On spectral analysis of directed signed graphs. Int. J. Data Sci. Anal. Yuemeng Li, Shuhan Yuan, Xintao Wu, Aidong Lu
2018	J	`jnl`	One-Class Adversarial Nets for Fraud Detection. CoRR Panpan Zheng, Shuhan Yuan, Xintao Wu, Jun Li, Aidong Lu
2018	J	`jnl`	SAFE: A Neural Survival Analysis Model for Fraud Early Detection. CoRR Panpan Zheng, Shuhan Yuan, Xintao Wu
2018	J	`jnl`	Task-specific word identification from short texts using a convolutional neural network. Intell. Data Anal. Shuhan Yuan, Xintao Wu, Yang Xiang
2017	A*	`conf`	A Causal Framework for Discovering and Removing Direct and Indirect Discrimination. IJCAI Lu Zhang, Yongkai Wu, Xintao Wu
2017	A*	`conf`	Achieving Non-Discrimination in Data Release. KDD Lu Zhang, Yongkai Wu, Xintao Wu
2017	J	`jnl`	Achieving non-discrimination in prediction. CoRR Lu Zhang, Yongkai Wu, Xintao Wu
2017	A*	`conf`	Adaptive Laplace Mechanism: Differential Privacy Preservation in Deep Learning. ICDM NhatHai Phan, Xintao Wu, Han Hu, Dejing Dou
2017	J	`jnl`	Adaptive Laplace Mechanism: Differential Privacy Preservation in Deep Learning. CoRR NhatHai Phan, Xintao Wu, Han Hu, Dejing Dou
2017	J	`jnl`	Anti-discrimination learning: a causal modeling-based framework. Int. J. Data Sci. Anal. Lu Zhang, Xintao Wu
2017	—	`conf`	DPWeka: Achieving Differential Privacy in WEKA. PAC Srinidhi Katla, Depeng Xu, Yongkai Wu, Qiuping Pan, Xintao Wu
2017	—	`conf`	Differential Privacy Preserving Causal Graph Discovery. PAC Depeng Xu, Shuhan Yuan, Xintao Wu
2017	—	`conf`	Modeling SNP and quantitative trait association from GWAS catalog using CLG Bayesian network. BIBM Lu Zhang, Qiuping Pan, Xintao Wu
2017	B	`conf`	On Spectral Analysis of Directed Signed Graphs. DSAA Yuemeng Li, Xintao Wu, Aidong Lu
2017	J	`jnl`	On Spectral Analysis of Signed and Dispute Graphs: Application to Community Structure. IEEE Trans. Knowl. Data Eng. Leting Wu, Xintao Wu, Aidong Lu, Yuemeng Li
2017	J	`jnl`	Preserving Differential Privacy in Convolutional Deep Belief Networks. CoRR NhatHai Phan, Xintao Wu, Dejing Dou
2017	J	`jnl`	Preserving differential privacy in convolutional deep belief networks. Mach. Learn. NhatHai Phan, Xintao Wu, Dejing Dou
2017	—	`conf`	SNE: Signed Network Embedding. PAKDD (2) Shuhan Yuan, Xintao Wu, Yang Xiang
2017	J	`jnl`	SNE: Signed Network Embedding. CoRR Shuhan Yuan, Xintao Wu, Yang Xiang
2017	—	`conf`	STIP: An SNP-trait inference platform. BIBM Qiuping Pan, Lu Zhang, Xintao Wu
2017	A	`conf`	Spectrum-based Deep Neural Networks for Fraud Detection. CIKM Shuhan Yuan, Xintao Wu, Jun Li, Aidong Lu
2017	J	`jnl`	Spectrum-based deep neural networks for fraud detection. CoRR Shuhan Yuan, Xintao Wu, Jun Li, Aidong Lu
2017	J	`jnl`	Task-specific Word Identification from Short Texts Using a Convolutional Neural Network. CoRR Shuhan Yuan, Xintao Wu, Yang Xiang
2017	—	`conf`	Wikipedia Vandal Early Detection: From User Behavior to User Embedding. ECML/PKDD (1) Shuhan Yuan, Panpan Zheng, Xintao Wu, Yang Xiang
2017	J	`jnl`	Wikipedia Vandal Early Detection: from User Behavior to User Embedding. CoRR Shuhan Yuan, Panpan Zheng, Xintao Wu, Yang Xiang
2016	—	`conf`	A Framework of Privacy Decision Recommendation for Image Sharing in Online Social Networks. DSC Donghui Hu, Fan Chen, Xintao Wu, Zhong-Qiu Zhao
2016	B	`conf`	A Two Phase Deep Learning Model for Identifying Discrimination from Tweets. EDBT Shuhan Yuan, Xintao Wu, Yang Xiang
2016	J	`jnl`	A causal framework for discovering and removing direct and indirect discrimination. CoRR Lu Zhang, Yongkai Wu, Xintao Wu
2016	J	`jnl`	Achieving non-discrimination in data release. CoRR Lu Zhang, Yongkai Wu, Xintao Wu
2016	—	`conf`	Building Bayesian networks from GWAS statistics based on Independence of Causal Influence. BIBM Lu Zhang, Qiuping Pan, Xintao Wu, Xinghua Shi
2016	A*	`conf`	Differential Privacy Preservation for Deep Auto-Encoders: an Application of Human Behavior Prediction. AAAI NhatHai Phan, Yue Wang, Xintao Wu, Dejing Dou
2016	A*	`conf`	Incorporating Pre-Training in Long Short-Term Memory Networks for Tweets Classification. ICDM Shuhan Yuan, Xintao Wu, Yang Xiang
2016	—	`conf`	Infringement of Individual Privacy via Mining Differentially Private GWAS Statistics. BigCom Yue Wang, Jia Wen, Xintao Wu, Xinghua Shi
2016	—	`conf`	On Discrimination Discovery Using Causal Networks. SBP-BRiMS Lu Zhang, Yongkai Wu, Xintao Wu
2016	J	`jnl`	On Spectral Analysis of Directed Signed Graphs. CoRR Yuemeng Li, Xintao Wu, Aidong Lu
2016	J	`jnl`	On digital image trustworthiness. Appl. Soft Comput. Donghui Hu, Xiaotian Zhang, Yuqi Fan, Zhong-Qiu Zhao, Lina Wang, Xintao Wu, Xindong Wu
2016	A*	`conf`	Situation Testing-Based Discrimination Discovery: A Causal Inference Approach. IJCAI Lu Zhang, Yongkai Wu, Xintao Wu
2016	B	`conf`	Social network dominance based on analysis of asymmetry. ASONAM Yuemeng Li, Xintao Wu, Song Yang
2016	B	`conf`	Using Loglinear Model for Discrimination Discovery and Prevention. DSAA Yongkai Wu, Xintao Wu
2016	—	`conf`	Using Randomized Response for Differential Privacy Preserving Data Collection. EDBT/ICDT Workshops Yue Wang, Xintao Wu, Donghui Hu
2015	A*	`conf`	Analysis of Spectral Space Properties of Directed Graphs Using Matrix Perturbation Theory with Application in Graph Partition. ICDM Yuemeng Li, Xintao Wu, Aidong Lu
2015	—	`conf`	Block-Organized Topology Visualization for Visual Exploration of Signed Networks. ICDM Workshops Xianlin Hu, Leting Wu, Aidong Lu, Xintao Wu
2015	J	`jnl`	Guest Editorial for Special Section on BIBM 2013. IEEE ACM Trans. Comput. Biol. Bioinform. Feng Luo, Xintao Wu
2015	—	`conf`	On Burst Detection and Prediction in Retweeting Sequence. PAKDD (1) Zhilin Luo, Yue Wang, Xintao Wu, Wandong Cai, Ting Chen
2015	J	`jnl`	Pairwised Specific Distance Learning from Physical Linkages. ACM Trans. Knowl. Discov. Data Ju-Hua Hu, De-Chuan Zhan, Xintao Wu, Yuan Jiang, Zhi-Hua Zhou
2015	J	`jnl`	Program-input generation for testing database applications using existing database states. Autom. Softw. Eng. Kai Pan, Xintao Wu, Tao Xie
2015	A*	`conf`	Regression Model Fitting under Differential Privacy and Model Inversion Attack. IJCAI Yue Wang, Cheng Si, Xintao Wu
2015	J	`jnl`	Security and privacy protocols for perceptual image hashing. Int. J. Sens. Networks Donghui Hu, Bin Su, Shuli Zheng, Zhong-Qiu Zhao, Xintao Wu, Xindong Wu
2014	J	`jnl`	Guided test generation for database applications via synthesized database interactions. ACM Trans. Softw. Eng. Methodol. Kai Pan, Xintao Wu, Tao Xie
2014	A*	`conf`	On Spectral Analysis of Signed and Dispute Graphs. ICDM Leting Wu, Xintao Wu, Aidong Lu, Yuemeng Li
2013	J	`jnl`	A spectral approach to detecting subtle anomalies in graphs. J. Intell. Inf. Syst. Leting Wu, Xintao Wu, Aidong Lu, Zhi-Hua Zhou
2013	—	`conf`	Automatic test generation for mutation testing on database applications. AST@ICSE Kai Pan, Xintao Wu, Tao Xie
2013	—	`conf`	Differential Privacy Preserving Spectral Graph Analysis. PAKDD (2) Yue Wang, Xintao Wu, Leting Wu
2013	—	`conf`	On Linear Refinement of Differential Privacy-Preserving Query Answering. PAKDD (2) Xiaowei Ying, Xintao Wu, Yue Wang
2013	J	`jnl`	On learning cluster coefficient of private networks. Soc. Netw. Anal. Min. Yue Wang, Xintao Wu, Jun Zhu, Yang Xiang
2013	J	`jnl`	Preserving Differential Privacy in Degree-Correlation based Graph Generation. Trans. Data Priv. Yue Wang, Xintao Wu
2013	J	`jnl`	Spectrum-Based Network Visualization for Topology Analysis. IEEE Computer Graphics and Applications Xianlin Hu, Aidong Lu, Xintao Wu
2013	—	`conf`	Using aggregate human genome data for individual identification. BIBM Yue Wang, Xintao Wu, Xinghua Shi
2012	J	`jnl`	Approximate Inverse Frequent Itemset Mining: Privacy, Complexity, and Approximation CoRR Yongge Wang, Xintao Wu
2012	B	`conf`	Examining Multi-factor Interactions in Microblogging Based on Log-linear Modeling. ASONAM Zhilin Luo, Xintao Wu, Wandong Cai, Dong Peng
2012	J	`jnl`	Examining spectral space of complex networks with positive and negative links. Int. J. Soc. Netw. Min. Leting Wu, Xiaowei Ying, Xintao Wu, Aidong Lu, Zhi-Hua Zhou
2012	B	`conf`	On Learning Cluster Coefficient of Private Networks. ASONAM Yue Wang, Xintao Wu, Jun Zhu, Yang Xiang
2012	B	`conf`	Predicting Retweeting Behavior Based on Autoregressive Moving Average Model. WISE Zhilin Luo, Yue Wang, Xintao Wu
2011	J	`jnl`	A Spectrum-Based Framework for Quantifying Randomness of Social Networks. IEEE Trans. Knowl. Data Eng. Xiaowei Ying, Leting Wu, Xintao Wu
2011	—	`conf`	Database state generation via dynamic symbolic execution for coverage criteria. DBTest Kai Pan, Xintao Wu, Tao Xie
2011	A*	`conf`	Generating program inputs for database application testing. ASE Kai Pan, Xintao Wu, Tao Xie
2011	J	`jnl`	Limiting Attribute Disclosure in Randomization Based Microdata Release. J. Comput. Sci. Eng. Ling Guo, Xiaowei Ying, Xintao Wu
2011	A*	`conf`	Line Orthogonality in Adjacency Eigenspace with Application to Community Partition. IJCAI Leting Wu, Xiaowei Ying, Xintao Wu, Zhi-Hua Zhou
2011	J	`jnl`	On link privacy in randomizing social networks. Knowl. Inf. Syst. Xiaowei Ying, Xintao Wu
2011	—	`conf`	Spectral Analysis of PAKDD (2) Leting Wu, Xiaowei Ying, Xintao Wu, Aidong Lu, Zhi-Hua Zhou
2011	A*	`conf`	Spectrum based fraud detection in social networks. ICDE Xiaowei Ying, Xintao Wu, Daniel Barbará
2010	—	`ch.`	A Survey of Privacy-Preservation of Graphs and Social Networks. Managing and Mining Graph Data Xintao Wu, Xiaowei Ying, Kun Liu, Lei Chen
2010	C	`conf`	Interactive detection of network anomalies via coordinated multiple views. VizSEC Lane Harrison, Xianlin Hu, Xiaowei Ying, Aidong Lu, Weichao Wang, Xintao Wu
2010	—	`conf`	On Attribute Disclosure in Randomization Based Privacy Preserving Data Publishing. ICDM Workshops Ling Guo, Xiaowei Ying, Xintao Wu
2010	A	`conf`	Reconstruction from Randomized Graph via Low Rank Approximation. SDM Leting Wu, Xiaowei Ying, Xintao Wu
2010	A*	`conf`	Spectrum based fraud detection in social networks. CCS Xiaowei Ying, Xintao Wu, Daniel Barbará
2009	—	`conf`	Comparisons of randomization and K-degree anonymization schemes for privacy preserving social network publishing. SNAKDD Xiaowei Ying, Kai Pan, Xintao Wu, Ling Guo
2009	A	`conf`	Graph Generation with Prescribed Feature Constraints. SDM Xiaowei Ying, Xintao Wu
2009	B	`conf`	On Link Privacy in Randomizing Social Networks. PAKDD Xiaowei Ying, Xintao Wu
2009	A	`conf`	On Randomness Measures for Social Networks. SDM Xiaowei Ying, Xintao Wu
2009	—	`ch.`	On the Quantification of Identity and Link Disclosures in Randomizing Social Networks. Advances in Information and Intelligent Systems Xiaowei Ying, Xintao Wu, Kai Pan, Ling Guo
2009	J	`jnl`	Privacy Preserving Categorical Data Analysis with Unknown Distortion Parameters. Trans. Data Priv. Ling Guo, Xintao Wu
2008	J	`jnl`	Determining error bounds for spectral filtering based reconstruction methods in privacy preserving data mining. Knowl. Inf. Syst. Songtao Guo, Xintao Wu, Yingjiu Li
2008	B	`conf`	On Addressing Accuracy Concerns in Privacy Preserving Association Rule Mining. PAKDD Ling Guo, Songtao Guo, Xintao Wu
2008	J	`jnl`	Protecting business intelligence and customer privacy while outsourcing data mining tasks. Knowl. Inf. Syst. Ling Qiu, Yingjiu Li, Xintao Wu
2008	A	`conf`	Randomizing Social Networks: a Spectrum Preserving Approach. SDM Xiaowei Ying, Xintao Wu
2007	B	`conf`	Deriving Private Information from Arbitrarily Projected Data. PAKDD Songtao Guo, Xintao Wu
2007	J	`jnl`	Preserving privacy in association rule mining with bloom filters. J. Intell. Inf. Syst. Ling Qiu, Yingjiu Li, Xintao Wu
2007	J	`jnl`	Privacy Preserving Database Generation for Database Application Testing. Fundam. Informaticae Xintao Wu, Yongge Wang, Songtao Guo, Yuliang Zheng
2007	—	`conf`	Privacy Preserving Market Basket Data Analysis. PKDD Ling Guo, Songtao Guo, Xintao Wu
2006	—	`conf`	An Approach to Outsourcing Data Mining Tasks while Protecting Business Intelligence and Customer Privacy. ICDM Workshops Ling Qiu, Yingjiu Li, Xintao Wu
2006	—	`conf`	Deriving Private Information from Perturbed Data Using IQR Based Approach. ICDE Workshops Songtao Guo, Xintao Wu, Yingjiu Li
2006	C	`conf`	Disclosure Analysis for Two-Way Contingency Tables. Privacy in Statistical Databases Haibing Lu, Yingjiu Li, Xintao Wu
2006	Misc	`conf`	Disclosure Risk in Dynamic Two-Dimensional Contingency Tables (Extended Abstract). ICISS Haibing Lu, Yingjiu Li, Xintao Wu
2006	J	`jnl`	Exploring gene causal interactions using an enhanced constraint-based method. Pattern Recognit. Xintao Wu, Yong Ye
2006	J	`jnl`	Incorporating large unlabeled data to enhance EM classification. J. Intell. Inf. Syst. Xintao Wu
2006	—	`conf`	On the Lower Bound of Reconstruction Error for Spectral Filtering Based Privacy Preserving Data Mining. PKDD Songtao Guo, Xintao Wu, Yingjiu Li
2006	Misc	`conf`	On the use of spectral filtering for privacy preserving data mining. SAC Songtao Guo, Xintao Wu
2006	Misc	`conf`	Towards value disclosure analysis in modeling general databases. SAC Xintao Wu, Songtao Guo, Yingjiu Li
2005	A*	`conf`	Approximate Inverse Frequent Itemset Mining: Privacy, Complexity, and Approximation. ICDM Yongge Wang, Xintao Wu
2005	C	`conf`	Efficient Causal Interaction Learning with Applications in Microarray. ISMIS Yong Ye, Xintao Wu
2005	C	`conf`	Privacy Aware Data Generation for Testing Database Applications. IDEAS Xintao Wu, Chintan Sanghvi, Yongge Wang, Yuliang Zheng
2005	A	`conf`	Privacy Aware Market Basket Data Set Generation: A Feasible Approach for Inverse Frequent Set Mining. SDM Xintao Wu, Ying Wu, Yongge Wang, Yingjiu Li
2005	C	`conf`	Statistical Database Modeling for Privacy Preserving Database Generation. ISMIS Xintao Wu, Yongge Wang, Yuliang Zheng
2004	A*	`conf`	GenExplore: Interactive Exploration of Gene Interactions from Microarray Data. ICDE Yong Ye, Xintao Wu, Kalpathi R. Subramanian, Liying Zhang
2004	B	`conf`	Privacy Preserving Data Generation for Database Application Performance Testing. TrustBus Yongge Wang, Xintao Wu, Yuliang Zheng
2003	J	`jnl`	An Approximate Median Polish Algorithm for Large Multidimensional Data Sets. Knowl. Inf. Syst. Daniel Barbará, Xintao Wu
2003	B	`conf`	Compressing High Dimensional Datasets by Fractals. DCC Xintao Wu, Daniel Barbará
2003	J	`jnl`	Graphical modeling based gene interaction analysis for microarray data. SIGKDD Explor. Xintao Wu, Yong Ye, Liying Zhang
2003	—	`conf`	Interactive Analysis of Gene Interactions Using Graphical gaussian model. BIOKDD Xintao Wu, Yong Ye, Kalpathi R. Subramanian
2003	—	`conf`	Privacy preserving database application testing. WPES Xintao Wu, Yongge Wang, Yuliang Zheng
2003	A*	`conf`	Screening and interpreting multi-item associations based on log-linear modeling. KDD Xintao Wu, Daniel Barbará, Yong Ye
2002	A*	`conf`	B-EM: a classifier incorporating bootstrap with EM approach for data mining. KDD Xintao Wu, Jianping Fan, Kalpathi R. Subramanian
2002	J	`jnl`	Learning missing values from summary constraints. SIGKDD Explor. Xintao Wu, Daniel Barbará
2002	B	`conf`	Modeling and Imputation of Large Incomplete Multidimensional Datasets. DaWaK Xintao Wu, Daniel Barbará
2001	—	`conf`	Finding Dense Clusters in Hyperspace: An Approach Based on Row Shuffling. WAIM Daniel Barbará, Xintao Wu
2001	J	`jnl`	Loglinear-Based Quasi Cubes. J. Intell. Inf. Syst. Daniel Barbará, Xintao Wu
2000	B	`conf`	Supporting Online Queries in ROLAP. DaWaK Daniel Barbará, Xintao Wu
2000	—	`conf`	Using Loglinear Models to Compress Datacube. Web-Age Information Management Daniel Barbará, Xintao Wu
1999	J	`jnl`	The Role of Approximations in Maintaining and Using Aggregate Views. IEEE Data Eng. Bull. Daniel Barbará, Xintao Wu
1999	A*	`conf`	Using Approximations to Scale Exploratory Data Analysis in Datacubes. KDD Daniel Barbará, Xintao Wu