Using Approximations to Scale Exploratory Data Analysis in Datacubes. - Daniel Barbará; Xintao Wu (KDD, 1999)

The Role of Approximations in Maintaining and Using Aggregate Views. - Daniel Barbará; Xintao Wu (IEEE Data Eng. Bull., 1999)

Supporting Online Queries in ROLAP. - Daniel Barbará; Xintao Wu (DaWaK, 2000)

Using Loglinear Models to Compress Datacube. - Daniel Barbará; Xintao Wu (Web-Age Information Management, 2000)

Finding Dense Clusters in Hyperspace: An Approach Based on Row Shuffling. - Daniel Barbará; Xintao Wu (WAIM, 2001)

Loglinear-Based Quasi Cubes. - Daniel Barbará; Xintao Wu (J. Intell. Inf. Syst., 2001)

Modeling and Imputation of Large Incomplete Multidimensional Datasets. - Xintao Wu; Daniel Barbará (DaWaK, 2002)

B-EM: a classifier incorporating bootstrap with EM approach for data mining. - Xintao Wu; Jianping Fan 001; Kalpathi R. Subramanian (KDD, 2002)

Learning missing values from summary constraints. - Xintao Wu; Daniel Barbará (SIGKDD Explor., 2002)

Compressing High Dimensional Datasets by Fractals. - Xintao Wu; Daniel Barbará (DCC, 2003)

Screening and interpreting multi-item associations based on log-linear modeling. - Xintao Wu; Daniel Barbará; Yong Ye (KDD, 2003)

Interactive Analysis of Gene Interactions Using Graphical gaussian model. - Xintao Wu; Yong Ye; Kalpathi R. Subramanian (BIOKDD, 2003)

Privacy preserving database application testing. - Xintao Wu; Yongge Wang 001; Yuliang Zheng 001 (WPES, 2003)

An Approximate Median Polish Algorithm for Large Multidimensional Data Sets. - Daniel Barbará; Xintao Wu (Knowl. Inf. Syst., 2003)

Graphical modeling based gene interaction analysis for microarray data. - Xintao Wu; Yong Ye; Liying Zhang (SIGKDD Explor., 2003)

GenExplore: Interactive Exploration of Gene Interactions from Microarray Data. - Yong Ye; Xintao Wu; Kalpathi R. Subramanian; Liying Zhang (ICDE, 2004)

Privacy Preserving Data Generation for Database Application Performance Testing. - Yongge Wang 001; Xintao Wu; Yuliang Zheng 001 (TrustBus, 2004)

Approximate Inverse Frequent Itemset Mining: Privacy, Complexity, and Approximation. - Yongge Wang 001; Xintao Wu (ICDM, 2005)

Privacy Aware Data Generation for Testing Database Applications. - Xintao Wu; Chintan Sanghvi; Yongge Wang 001; Yuliang Zheng 001 (IDEAS, 2005)

Statistical Database Modeling for Privacy Preserving Database Generation. - Xintao Wu; Yongge Wang 001; Yuliang Zheng 001 (ISMIS, 2005)

Efficient Causal Interaction Learning with Applications in Microarray. - Yong Ye; Xintao Wu (ISMIS, 2005)

Privacy Aware Market Basket Data Set Generation: A Feasible Approach for Inverse Frequent Set Mining. - Xintao Wu; Ying Wu; Yongge Wang 001; Yingjiu Li (SDM, 2005)

Deriving Private Information from Perturbed Data Using IQR Based Approach. - Songtao Guo; Xintao Wu; Yingjiu Li (ICDE Workshops, 2006)

An Approach to Outsourcing Data Mining Tasks while Protecting Business Intelligence and Customer Privacy. - Ling Qiu; Yingjiu Li; Xintao Wu (ICDM Workshops, 2006)

Disclosure Risk in Dynamic Two-Dimensional Contingency Tables (Extended Abstract). - Haibing Lu; Yingjiu Li; Xintao Wu (ICISS, 2006)

On the Lower Bound of Reconstruction Error for Spectral Filtering Based Privacy Preserving Data Mining. - Songtao Guo; Xintao Wu; Yingjiu Li (PKDD, 2006)

Disclosure Analysis for Two-Way Contingency Tables. - Haibing Lu; Yingjiu Li; Xintao Wu (Privacy in Statistical Databases, 2006)

On the use of spectral filtering for privacy preserving data mining. - Songtao Guo; Xintao Wu (SAC, 2006)

Towards value disclosure analysis in modeling general databases. - Xintao Wu; Songtao Guo; Yingjiu Li (SAC, 2006)

Incorporating large unlabeled data to enhance EM classification. - Xintao Wu (J. Intell. Inf. Syst., 2006)

Exploring gene causal interactions using an enhanced constraint-based method. - Xintao Wu; Yong Ye (Pattern Recognit., 2006)

Deriving Private Information from Arbitrarily Projected Data. - Songtao Guo; Xintao Wu (PAKDD, 2007)

Privacy Preserving Market Basket Data Analysis. - Ling Guo; Songtao Guo; Xintao Wu (PKDD, 2007)

Privacy Preserving Database Generation for Database Application Testing. - Xintao Wu; Yongge Wang 001; Songtao Guo; Yuliang Zheng 001 (Fundam. Informaticae, 2007)

Preserving privacy in association rule mining with bloom filters. - Ling Qiu; Yingjiu Li; Xintao Wu (J. Intell. Inf. Syst., 2007)

On Addressing Accuracy Concerns in Privacy Preserving Association Rule Mining. - Ling Guo; Songtao Guo; Xintao Wu (PAKDD, 2008)

Randomizing Social Networks: a Spectrum Preserving Approach. - Xiaowei Ying; Xintao Wu (SDM, 2008)

Determining error bounds for spectral filtering based reconstruction methods in privacy preserving data mining. - Songtao Guo; Xintao Wu; Yingjiu Li (Knowl. Inf. Syst., 2008)

Protecting business intelligence and customer privacy while outsourcing data mining tasks. - Ling Qiu; Yingjiu Li; Xintao Wu (Knowl. Inf. Syst., 2008)

Comparisons of randomization and K-degree anonymization schemes for privacy preserving social network publishing. - Xiaowei Ying; Kai Pan; Xintao Wu; Ling Guo (SNAKDD, 2009)

On Randomness Measures for Social Networks. - Xiaowei Ying; Xintao Wu (SDM, 2009)

Graph Generation with Prescribed Feature Constraints. - Xiaowei Ying; Xintao Wu (SDM, 2009)

Privacy Preserving Categorical Data Analysis with Unknown Distortion Parameters. - Ling Guo; Xintao Wu (Trans. Data Priv., 2009)

On the Quantification of Identity and Link Disclosures in Randomizing Social Networks. - Xiaowei Ying; Xintao Wu; Kai Pan; Ling Guo (Advances in Information and Intelligent Systems, 2009)

Spectrum based fraud detection in social networks. - Xiaowei Ying; Xintao Wu; Daniel Barbará (CCS, 2010)

On Attribute Disclosure in Randomization Based Privacy Preserving Data Publishing. - Ling Guo; Xiaowei Ying; Xintao Wu (ICDM Workshops, 2010)

Reconstruction from Randomized Graph via Low Rank Approximation. - Leting Wu; Xiaowei Ying; Xintao Wu (SDM, 2010)

Interactive detection of network anomalies via coordinated multiple views. - Lane Harrison; Xianlin Hu; Xiaowei Ying; Aidong Lu; Weichao Wang; Xintao Wu (VizSEC, 2010)

A Survey of Privacy-Preservation of Graphs and Social Networks. - Xintao Wu; Xiaowei Ying; Kun Liu 001; Lei Chen 002 (Managing and Mining Graph Data, 2010)

Line Orthogonality in Adjacency Eigenspace with Application to Community Partition. - Leting Wu; Xiaowei Ying; Xintao Wu; Zhi-Hua Zhou (IJCAI, 2011)

Generating program inputs for database application testing. - Kai Pan; Xintao Wu; Tao Xie 001 (ASE, 2011)

Spectral Analysis of k-Balanced Signed Graphs. - Leting Wu; Xiaowei Ying; Xintao Wu; Aidong Lu; Zhi-Hua Zhou (PAKDD (2), 2011)

Database state generation via dynamic symbolic execution for coverage criteria. - Kai Pan; Xintao Wu; Tao Xie 001 (DBTest, 2011)

Limiting Attribute Disclosure in Randomization Based Microdata Release. - Ling Guo; Xiaowei Ying; Xintao Wu (J. Comput. Sci. Eng., 2011)

On link privacy in randomizing social networks. - Xiaowei Ying; Xintao Wu (Knowl. Inf. Syst., 2011)

A Spectrum-Based Framework for Quantifying Randomness of Social Networks. - Xiaowei Ying; Leting Wu; Xintao Wu (IEEE Trans. Knowl. Data Eng., 2011)

Examining Multi-factor Interactions in Microblogging Based on Log-linear Modeling. - Zhilin Luo; Xintao Wu; Wandong Cai; Dong Peng (ASONAM, 2012)

Predicting Retweeting Behavior Based on Autoregressive Moving Average Model. - Zhilin Luo; Yue Wang 009; Xintao Wu (WISE, 2012)

Examining spectral space of complex networks with positive and negative links. - Leting Wu; Xiaowei Ying; Xintao Wu; Aidong Lu; Zhi-Hua Zhou (Int. J. Soc. Netw. Min., 2012)

Using aggregate human genome data for individual identification. - Yue Wang 009; Xintao Wu; Xinghua Shi (BIBM, 2013)

Automatic test generation for mutation testing on database applications. - Kai Pan; Xintao Wu; Tao Xie 001 (AST, 2013)

Differential Privacy Preserving Spectral Graph Analysis. - Yue Wang 009; Xintao Wu; Leting Wu (PAKDD (2), 2013)

On Linear Refinement of Differential Privacy-Preserving Query Answering. - Xiaowei Ying; Xintao Wu; Yue Wang 009 (PAKDD (2), 2013)

Spectrum-Based Network Visualization for Topology Analysis. - Xianlin Hu; Aidong Lu; Xintao Wu (IEEE Computer Graphics and Applications, 2013)

A spectral approach to detecting subtle anomalies in graphs. - Leting Wu; Xintao Wu; Aidong Lu; Zhi-Hua Zhou (J. Intell. Inf. Syst., 2013)

On learning cluster coefficient of private networks. - Yue Wang 009; Xintao Wu; Jun Zhu 002; Yang Xiang 006 (Soc. Netw. Anal. Min., 2013)

Preserving Differential Privacy in Degree-Correlation based Graph Generation. - Yue Wang 009; Xintao Wu (Trans. Data Priv., 2013)

On Spectral Analysis of Signed and Dispute Graphs. - Leting Wu; Xintao Wu; Aidong Lu; Yuemeng Li (ICDM, 2014)

Guided test generation for database applications via synthesized database interactions. - Kai Pan; Xintao Wu; Tao Xie 001 (ACM Trans. Softw. Eng. Methodol., 2014)

Block-Organized Topology Visualization for Visual Exploration of Signed Networks. - Xianlin Hu; Leting Wu; Aidong Lu; Xintao Wu (ICDM Workshops, 2015)

Analysis of Spectral Space Properties of Directed Graphs Using Matrix Perturbation Theory with Application in Graph Partition. - Yuemeng Li; Xintao Wu; Aidong Lu (ICDM, 2015)

Regression Model Fitting under Differential Privacy and Model Inversion Attack. - Yue Wang 009; Cheng Si; Xintao Wu (IJCAI, 2015)

On Burst Detection and Prediction in Retweeting Sequence. - Zhilin Luo; Yue Wang 009; Xintao Wu; Wandong Cai; Ting Chen 007 (PAKDD (1), 2015)

Program-input generation for testing database applications using existing database states. - Kai Pan; Xintao Wu; Tao Xie 001 (Autom. Softw. Eng., 2015)

Security and privacy protocols for perceptual image hashing. - Donghui Hu; Bin Su; Shuli Zheng; Zhong-Qiu Zhao; Xintao Wu; Xindong Wu 001 (Int. J. Sens. Networks, 2015)

Guest Editorial for Special Section on BIBM 2013. - Feng Luo 001; Xintao Wu (IEEE ACM Trans. Comput. Biol. Bioinform., 2015)

Pairwised Specific Distance Learning from Physical Linkages. - Ju-Hua Hu; De-Chuan Zhan; Xintao Wu; Yuan Jiang 001; Zhi-Hua Zhou (ACM Trans. Knowl. Discov. Data, 2015)

Differential Privacy Preservation for Deep Auto-Encoders: an Application of Human Behavior Prediction. - NhatHai Phan; Yue Wang 009; Xintao Wu; Dejing Dou (AAAI, 2016)

Social network dominance based on analysis of asymmetry. - Yuemeng Li; Xintao Wu; Song Yang (ASONAM, 2016)

Building Bayesian networks from GWAS statistics based on Independence of Causal Influence. - Lu Zhang 021; Qiuping Pan; Xintao Wu; Xinghua Shi (BIBM, 2016)

Infringement of Individual Privacy via Mining Differentially Private GWAS Statistics. - Yue Wang 009; Jia Wen; Xintao Wu; Xinghua Shi (BigCom, 2016)

Using Loglinear Model for Discrimination Discovery and Prevention. - Yongkai Wu; Xintao Wu (DSAA, 2016)

A Framework of Privacy Decision Recommendation for Image Sharing in Online Social Networks. - Donghui Hu; Fan Chen; Xintao Wu; Zhong-Qiu Zhao (DSC, 2016)

Using Randomized Response for Differential Privacy Preserving Data Collection. - Yue Wang 009; Xintao Wu; Donghui Hu (EDBT/ICDT Workshops, 2016)

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)

Situation Testing-Based Discrimination Discovery: A Causal Inference Approach. - Lu Zhang 021; Yongkai Wu; Xintao Wu (IJCAI, 2016)

On Discrimination Discovery Using Causal Networks. - Lu Zhang 021; Yongkai Wu; Xintao Wu (SBP-BRiMS, 2016)

On digital image trustworthiness. - Donghui Hu; Xiaotian Zhang; Yuqi Fan 001; Zhong-Qiu Zhao; Lina Wang 001; Xintao Wu; Xindong Wu 001 (Appl. Soft Comput., 2016)

STIP: An SNP-trait inference platform. - Qiuping Pan; Lu Zhang 021; Xintao Wu (BIBM, 2017)

Modeling SNP and quantitative trait association from GWAS catalog using CLG Bayesian network. - Lu Zhang 021; Qiuping Pan; Xintao Wu (BIBM, 2017)

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

On Spectral Analysis of Directed Signed Graphs. - Yuemeng Li; Xintao Wu; Aidong Lu (DSAA, 2017)

Adaptive Laplace Mechanism: Differential Privacy Preservation in Deep Learning. - NhatHai Phan; Xintao Wu; Han Hu 007; Dejing Dou (ICDM, 2017)

A Causal Framework for Discovering and Removing Direct and Indirect Discrimination. - Lu Zhang 021; Yongkai Wu; Xintao Wu (IJCAI, 2017)

Achieving Non-Discrimination in Data Release. - Lu Zhang 021; Yongkai Wu; Xintao Wu (KDD, 2017)

DPWeka: Achieving Differential Privacy in WEKA. - Srinidhi Katla; Depeng Xu 001; Yongkai Wu; Qiuping Pan; Xintao Wu (PAC, 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)

Anti-discrimination learning: a causal modeling-based framework. - Lu Zhang 021; Xintao Wu (Int. J. Data Sci. Anal., 2017)

Preserving differential privacy in convolutional deep belief networks. - NhatHai Phan; Xintao Wu; Dejing Dou (Mach. Learn., 2017)

On Spectral Analysis of Signed and Dispute Graphs: Application to Community Structure. - Leting Wu; Xintao Wu; Aidong Lu; Yuemeng Li (IEEE Trans. Knowl. Data Eng., 2017)

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

Achieving Non-Discrimination in Prediction. - Lu Zhang 021; Yongkai Wu; Xintao Wu (IJCAI, 2018)

On Discrimination Discovery and Removal in Ranked Data using Causal Graph. - Yongkai Wu; Lu Zhang 021; Xintao Wu (KDD, 2018)

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

Fairness-aware Classification: Criterion, Convexity, and Bounds. - Yongkai Wu; Lu Zhang 021; Xintao Wu (CoRR, 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)

BotFlowMon: Learning-based, Content-Agnostic Identification of Social Bot Traffic Flows. - Yebo Feng; Jun Li 001; Lei Jiao 002; Xintao Wu (CNS, 2019)

Heterogeneous Gaussian Mechanism: Preserving Differential Privacy in Deep Learning with Provable Robustness. - NhatHai Phan; Minh N. Vu; Yang Liu; Ruoming Jin; Dejing Dou; Xintao Wu; My T. Thai (IJCAI, 2019)

Counterfactual Fairness: Unidentification, Bound and Algorithm. - Yongkai Wu; Lu Zhang 021; Xintao Wu (IJCAI, 2019)

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

PC-Fairness: A Unified Framework for Measuring Causality-based Fairness. - Yongkai Wu; Lu Zhang 021; Xintao Wu; Hanghang Tong (NeurIPS, 2019)

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

Characteristics of Bitcoin Transactions on Cryptomarkets. - Xucan Chen; Mohammad Al Hasan; Xintao Wu; Pavel Skums; Mohammad Javad Feizollahi; Marie Ouellet; Eric L. Sevigny; David Maimon; Yubao Wu (SpaCCS, 2019)

On Convexity and Bounds of Fairness-aware Classification. - Yongkai Wu; Lu Zhang 021; Xintao Wu (WWW, 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)

Bayesian Network Construction and Genotype-Phenotype Inference Using GWAS Statistics. - Lu Zhang 021; Qiuping Pan; Yue Wang 009; Xintao Wu; Xinghua Shi (IEEE ACM Trans. Comput. Biol. Bioinform., 2019)

Causal Modeling-Based Discrimination Discovery and Removal: Criteria, Bounds, and Algorithms. - Lu Zhang 021; Yongkai Wu; Xintao Wu (IEEE Trans. Knowl. Data Eng., 2019)

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

AdvPL: Adversarial Personalized Learning. - Wei Du 009; Xintao Wu (DSAA, 2020)

Database-Access Performance Antipatterns in Database-Backed Web Applications. - Shudi Shao; Zhengyi Qiu; Xiao Yu; Wei Yang 013; Guoliang Jin; Tao Xie 001; Xintao Wu (ICSME, 2020)

Fair Multiple Decision Making Through Soft Interventions. - Yaowei Hu 001; Yongkai Wu; Lu Zhang 021; Xintao Wu (NeurIPS, 2020)

Multi-cause Discrimination Analysis Using Potential Outcomes. - Wen Huang 003; Yongkai Wu; Xintao Wu (SBP-BRiMS, 2020)

Fairness through Equality of Effort. - Wen Huang 003; Yongkai Wu; Lu Zhang 021; Xintao Wu (WWW (Companion Volume), 2020)

Removing Disparate Impact of Differentially Private Stochastic Gradient Descent on Model Accuracy. - Depeng Xu 001; Wei Du 009; Xintao Wu (CoRR, 2020)

A Generative Adversarial Framework for Bounding Confounded Causal Effects. - Yaowei Hu 001; Yongkai Wu; Lu Zhang 021; Xintao Wu (AAAI, 2021)

Classifying Math Knowledge Components via Task-Adaptive Pre-Trained BERT. - Jia Tracy Shen; Michiharu Yamashita; Ethan Prihar; Neil T. Heffernan; Xintao Wu; Sean McGrew; Dongwon Lee 001 (AIED (1), 2021)

Fairness-aware Bandit-based Recommendation. - Wen Huang 003; Kevin Labille; Xintao Wu; Dongwon Lee 001; Neil T. Heffernan (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)

Fair and Robust Classification Under Sample Selection Bias. - Wei Du 009; Xintao Wu (CIKM, 2021)

A Modeling and Verification Method of Modbus TCP/IP Protocol. - Jie Wang 004; Zhichao Chen; Gang Hou; Haoyu Gao; Pengfei Li; Ao Gao; Xintao Wu (ICA3PP (3), 2021)

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

Removing Disparate Impact on Model Accuracy in Differentially Private Stochastic Gradient Descent. - Depeng Xu 001; Wei Du 009; Xintao Wu (KDD, 2021)

Managing Uncertainty in Crowdsourcing with Interval-Valued Labels. - Chenyi Hu; Victor S. Sheng; Ningning Wu; Xintao Wu (NAFIPS, 2021)

Transferable Contextual Bandits with Prior Observations. - Kevin Labille; Wen Huang 003; Xintao Wu (PAKDD (2), 2021)

Fairness-aware Agnostic Federated Learning. - Wei Du 009; Depeng Xu 001; Xintao Wu; Hanghang Tong (SDM, 2021)

Attent: Active Attributed Network Alignment. - Qinghai Zhou; Liangyue Li; Xintao Wu; Nan Cao 001; Lei Ying 001; Hanghang Tong (WWW, 2021)

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

MultiFair: Multi-Group Fairness in Machine Learning. - Jian Kang 008; Tiankai Xie; Xintao Wu; Ross Maciejewski; Hanghang Tong (CoRR, 2021)

Classifying Math KCs via Task-Adaptive Pre-Trained BERT. - Jia Tracy Shen; Michiharu Yamashita; Ethan Prihar; Neil T. Heffernan; Xintao Wu; Sean McGrew; Dongwon Lee 001 (CoRR, 2021)

Robust Fairness-aware Learning Under Sample Selection Bias. - Wei Du 009; Xintao Wu (CoRR, 2021)

MathBERT: A Pre-trained Language Model for General NLP Tasks in Mathematics Education. - Jia Tracy Shen; Michiharu Yamashita; Ethan Prihar; Neil T. Heffernan; Xintao Wu; Dongwon Lee 001 (CoRR, 2021)

Enhancing personalized modeling via weighted and adversarial learning. - Wei Du 009; Xintao Wu (Int. J. Data Sci. Anal., 2021)

Towards Learning-Based, Content-Agnostic Detection of Social Bot Traffic. - Yebo Feng; Jun Li 001; Lei Jiao 002; Xintao Wu (IEEE Trans. Dependable Secur. Comput., 2021)

oGBAC - A Group Based Access Control Framework for Information Sharing in Online Social Networks. - Donghui Hu; Chunya Hu; Yuqi Fan 001; Xintao Wu (IEEE Trans. Dependable Secur. Comput., 2021)

Achieving Counterfactual Fairness for Causal Bandit. - Wen Huang 003; Lu Zhang 021; Xintao Wu (AAAI, 2022)

Fair Collective Classification in Networked Data. - Karuna Bhaila; Yongkai Wu; Xintao Wu (IEEE Big Data, 2022)

Robust Personalized Federated Learning under Demographic Fairness Heterogeneity. - Alycia N. Carey; Wei Du 009; Xintao Wu (IEEE Big Data, 2022)

Fair Regression under Sample Selection Bias. - Wei Du 009; Xintao Wu; Hanghang Tong (IEEE Big Data, 2022)

InfoFair: Information-Theoretic Intersectional Fairness. - Jian Kang 008; Tiankai Xie; Xintao Wu; Ross Maciejewski; Hanghang Tong (IEEE Big Data, 2022)

SCM-VAE: Learning Identifiable Causal Representations via Structural Knowledge. - Aneesh Komanduri; Yongkai Wu; Wen Huang 003; Feng Chen 001; Xintao Wu (IEEE Big Data, 2022)

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

Heterogeneous Randomized Response for Differential Privacy in Graph Neural Networks. - Khang Tran; Phung Lai; NhatHai Phan; Issa Khalil; Yao Ma 001; Abdallah Khreishah; My T. Thai; Xintao Wu (IEEE Big Data, 2022)

Defending Evasion Attacks via Adversarially Adaptive Training. - Minh-Hao Van; Wei Du 009; Xintao Wu; Feng Chen 001; Aidong Lu (IEEE Big Data, 2022)

Poisoning Attacks on Fair Machine Learning. - Minh-Hao Van; Wei Du 009; Xintao Wu; Aidong Lu (DASFAA (1), 2022)

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

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

1st ACM SIGKDD Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI-KDD22). - Chen Zhao 010; Feng Chen 001; Xintao Wu; Christopher Funk; Anthony Hoogs (KDD, 2022)

Adaptive Fairness-Aware Online Meta-Learning for Changing Environments. - Chen Zhao 010; Feng Mi; Xintao Wu; Kai Jiang; Latifur Khan; Feng Chen 001 (KDD, 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)

The Fairness Field Guide: Perspectives from Social and Formal Sciences. - Alycia N. Carey; Xintao Wu (CoRR, 2022)

Model Transferring Attacks to Backdoor HyperNetwork in Personalized Federated Learning. - Phung Lai; NhatHai Phan; Abdallah Khreishah; Issa Khalil; Xintao Wu (CoRR, 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)

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

The Causal Fairness Field Guide: Perspectives From Social and Formal Sciences. - Alycia N. Carey; Xintao Wu (Frontiers Big Data, 2022)

Modeling and reliability verification of industrial control network protocol based on time state transition matrix. - Jie Wang 004; Xintao Wu; Gang Hou; Pengfei Li; Ao Gao; Zhichao Chen; Haoyu Gao (Int. J. Commun. Syst., 2022)

Achieving User-Side Fairness in Contextual Bandits. - Wen Huang 003; Kevin Labille; Xintao Wu; Dongwon Lee 001; Neil T. Heffernan (Hum. Centric Intell. Syst., 2022)

Randomized Response Has No Disparate Impact on Model Accuracy. - Alycia N. Carey; Karuna Bhaila; Xintao Wu (IEEE Big Data, 2023)

Mitigating Confounding and Selection Biases in Personalized Recommendation: A Causal Approach. - Wen Huang 003; Jingbo Zhou; Xintao Wu; Dejing Dou (IEEE Big Data, 2023)

A Robust Classifier under Missing-Not-at-Random Sample Selection Bias. - Huy Mai; Wen Huang 003; Wei Du 009; Xintao Wu (IEEE Big Data, 2023)

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

HINT: Healthy Influential-Noise based Training to Defend against Data Poisoning Attacks. - Minh-Hao Van; Alycia N. Carey; Xintao Wu (ICDM, 2023)

2nd Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI). - Chen Zhao 010; Feng Chen 001; Xintao Wu; Haifeng Chen; Jiayu Zhou (KDD, 2023)

Towards Fair Disentangled Online Learning for Changing Environments. - Chen Zhao 010; Feng Mi; Xintao Wu; Kai Jiang; Latifur Khan; Christan Grant; Feng Chen 001 (KDD, 2023)

Investigating the Impact of Skill-Related Videos on Online Learning. - Ethan Prihar; Aaron Haim; Tracy Jia Shen; Adam Sales; Dongwon Lee 001; Xintao Wu; Neil T. Heffernan (L@S, 2023)

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

Detecting and Correcting Hate Speech in Multimodal Memes with Large Visual Language Model. - Minh-Hao Van; Xintao Wu (CoRR, 2023)

Fairness-Aware Domain Generalization under Covariate and Dependence Shifts. - Chen Zhao 010; Kai Jiang; Xintao Wu; Haoliang Wang; Latifur Khan; Christan Grant; Feng Chen 001 (CoRR, 2023)

The statistical fairness field guide: perspectives from social and formal sciences. - Alycia N. Carey; Xintao Wu (AI Ethics, 2023)

Robustly Improving Bandit Algorithms with Confounded and Selection Biased Offline Data: A Causal Approach. - Wen Huang 003; Xintao Wu (AAAI, 2024)

DP-TabICL: In-Context Learning with Differentially Private Tabular Data. - Alycia N. Carey; Karuna Bhaila; Kennedy Edemacu; Xintao Wu (IEEE Big Data, 2024)

Federated Learning under Sample Selection Heterogeneity. - Huy Mai; Xintao Wu (IEEE Big Data, 2024)

Beyond Human Vision: The Role of Large Vision Language Models in Microscope Image Analysis. - Prateek Verma; Minh-Hao Van; Xintao Wu (IEEE Big Data, 2024)

Content-Aware Deep Learning Recommender System. - Qixin Wang; Xintao Wu; Kan Yao; Han Li (IEEE Big Data, 2024)

On Large Visual Language Models for Medical Imaging Analysis: An Empirical Study. - Minh-Hao Van; Prateek Verma; Xintao Wu (CHASE, 2024)

Causal Diffusion Autoencoders: Toward Counterfactual Generation via Diffusion Probabilistic Models. - Aneesh Komanduri; Chen Zhao 010; Feng Chen 001; Xintao Wu (ECAI, 2024)

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

Learning Causally Disentangled Representations via the Principle of Independent Causal Mechanisms. - Aneesh Komanduri; Yongkai Wu; Feng Chen 001; Xintao Wu (IJCAI, 2024)

Supervised Algorithmic Fairness in Distribution Shifts: A Survey. - Minglai Shao 001; Dong Li 034; Chen Zhao 010; Xintao Wu; Yujie Lin; Qin Tian (IJCAI, 2024)

Cascading Failure Prediction in Power Grid Using Node and Edge Attributed Graph Neural Networks. - Karuna Bhaila; Xintao Wu (IJCNN, 2024)

Evaluating the Impact of Local Differential Privacy on Utility Loss via Influence Functions. - Alycia N. Carey; Minh-Hao Van; Xintao Wu (IJCNN, 2024)

On Prediction Feature Assignment in the Heckman Selection Model. - Huy Mai; Xintao Wu (IJCNN, 2024)

Algorithmic Fairness Generalization under Covariate and Dependence Shifts Simultaneously. - Chen Zhao 010; Kai Jiang; Xintao Wu; Haoliang Wang; Latifur Khan; Christan Grant; Feng Chen 001 (KDD, 2024)

3rd Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI). - Chen Zhao 010; Feng Chen 001; Xintao Wu; Jundong Li; Haifeng Chen (KDD, 2024)

Robust Influence-Based Training Methods for Noisy Brain MRI. - Minh-Hao Van; Alycia N. Carey; Xintao Wu (PKDD (4), 2024)

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

Local Differential Privacy in Graph Neural Networks: a Reconstruction Approach. - Karuna Bhaila; Wen Huang 003; Yongkai Wu; Xintao Wu (SDM, 2024)

In-Context Learning Demonstration Selection via Influence Analysis. - Vinay M. S.; Minh-Hao Van; Xintao Wu (CoRR, 2024)

Fair In-Context Learning via Latent Concept Variables. - Karuna Bhaila; Minh-Hao Van; Kennedy Edemacu; Chen Zhao 010; Feng Chen 001; Xintao Wu (CoRR, 2024)

From Identifiable Causal Representations to Controllable Counterfactual Generation: A Survey on Causal Generative Modeling. - Aneesh Komanduri; Xintao Wu; Yongkai Wu; Feng Chen 001 (Trans. Mach. Learn. Res., 2024)

Dynamic Environment Responsive Online Meta-Learning with Fairness Awareness. - Chen Zhao 010; Feng Mi; Xintao Wu; Kai Jiang; Latifur Khan; Feng Chen 001 (ACM Trans. Knowl. Discov. Data, 2024)

WSA-YOLOv5s: improved YOLOv5s based on window self-attention module for ship detection. - Weina Zhou; Hong Wang; Xintao Wu (Pattern Anal. Appl., 2024)

Let The Jury Decide: Fair Demonstration Selection for In-Context Learning through Incremental Greedy Evaluation. - Sadaf Md. Halim; Chen Zhao 010; Xintao Wu; Latifur Khan; Christan Grant; Fariha Ishrat Rahman; Feng Chen 001 (ACL (Findings), 2025)

Fairness-Aware Active Online Learning with Changing Environments. - Sadaf Md. Halim; Chen Zhao 010; Xintao Wu; Latifur Khan; Christan Earl Grant; Feng Chen 001 (ICDE, 2025)

Soft Prompting for Unlearning in Large Language Models. - Karuna Bhaila; Minh-Hao Van; Xintao Wu (NAACL (Long Papers), 2025)

A Survey on Computational Pathology Foundation Models: Datasets, Adaptation Strategies, and Evaluation Tasks. - Dong Li 034; Guihong Wan; Xintao Wu; Xinyu Wu; Ajit Johnson Nirmal; Christine G. Lian; Peter K. Sorger; Yevgeniy R. Semenov; Chen Zhao 010 (CoRR, 2025)

Multi-Modal Foundation Models for Computational Pathology: A Survey. - Dong Li 034; Guihong Wan; Xintao Wu; Xinyu Wu; Xiaohui Chen; Yi He; Christine G. Lian; Peter K. Sorger; Yevgeniy R. Semenov; Chen Zhao 010 (CoRR, 2025)

A Client-level Assessment of Collaborative Backdoor Poisoning in Non-IID Federated Learning. - Phung Lai; Guanxiong Liu; NhatHai Phan; Issa Khalil; Abdallah Khreishah; Xintao Wu (CoRR, 2025)

Achieving Distributive Justice in Federated Learning via Uncertainty Quantification. - Alycia N. Carey; Xintao Wu (CoRR, 2025)

Detecting and Mitigating Hateful Content in Multimodal Memes with Vision-Language Models. - Minh-Hao Van; Xintao Wu (CoRR, 2025)

CausalVLBench: Benchmarking Visual Causal Reasoning in Large Vision-Language Models. - Aneesh Komanduri; Karuna Bhaila; Xintao Wu (CoRR, 2025)

A Survey of AI for Materials Science: Foundation Models, LLM Agents, Datasets, and Tools. - Minh-Hao Van; Prateek Verma; Chen Zhao 010; Xintao Wu (CoRR, 2025)

AdaptJobRec: Enhancing Conversational Career Recommendation through an LLM-Powered Agentic System. - Qixin Wang; Dawei Wang; Kun Chen; Yaowei Hu 001; Puneet Girdhar; Ruoteng Wang; Aadesh Gupta; Chaitanya Devella; Wenlai Guo; Shangwen Huang; Bachir Aoun; Greg Hayworth; et al. (CoRR, 2025)

Privacy Preserving Prompt Engineering: A Survey. - Kennedy Edemacu; Xintao Wu (ACM Comput. Surv., 2025)