Xintao Wu

ORCID

Publication Activity (10 Years)

Years Active: 1999-2024
Publications (10 Years): 176

Top Venues

Publications

Karuna Bhaila, Wen Huang, Yongkai Wu, Xintao Wu
Local Differential Privacy in Graph Neural Networks: a Reconstruction Approach. SDM (2024)
Kennedy Edemacu, Xintao Wu
Privacy Preserving Prompt Engineering: A Survey. CoRR (2024)
Karuna Bhaila, Minh-Hao Van, Xintao Wu
Soft Prompting for Unlearning in Large Language Models. CoRR (2024)
Minh-Hao Van, Prateek Verma, Xintao Wu
On Large Visual Language Models for Medical Imaging Analysis: An Empirical Study. CHASE (2024)
Minh-Hao Van, Prateek Verma, Xintao Wu
On Large Visual Language Models for Medical Imaging Analysis: An Empirical Study. CoRR (2024)
Yujie Lin, Dong Li, Chen Zhao, Xintao Wu, Qin Tian, Minglai Shao
Supervised Algorithmic Fairness in Distribution Shifts: A Survey. CoRR (2024)
Alycia N. Carey, Karuna Bhaila, Kennedy Edemacu, Xintao Wu
DP-TabICL: In-Context Learning with Differentially Private Tabular Data. CoRR (2024)
Chen Zhao, Kai Jiang, Xintao Wu, Haoliang Wang, Latifur Khan, Christan Grant, Feng Chen
Algorithmic Fairness Generalization under Covariate and Dependence Shifts Simultaneously. KDD (2024)
Prateek Verma, Minh-Hao Van, Xintao Wu
Beyond Human Vision: The Role of Large Vision Language Models in Microscope Image Analysis. CoRR (2024)
Wen Huang, Xintao Wu
Robustly Improving Bandit Algorithms with Confounded and Selection Biased Offline Data: A Causal Approach. AAAI (2024)
Vinay M. S., Shuhan Yuan, Xintao Wu
Contrastive Learning for Fraud Detection from Noisy Labels. ICDE (2024)
Vinay M. S., Minh-Hao Van, Xintao Wu
In-Context Learning Demonstration Selection via Influence Analysis. CoRR (2024)
Chen Zhao, Feng Mi, Xintao Wu, Kai Jiang, Latifur Khan, Feng Chen
Dynamic Environment Responsive Online Meta-Learning with Fairness Awareness. ACM Trans. Knowl. Discov. Data 18 (6) (2024)
Minh-Hao Van, Alycia N. Carey, Xintao Wu
Robust Influence-Based Training Methods for Noisy Brain MRI. PKDD (4) (2024)
Chen Zhao, Feng Chen, Xintao Wu, Jundong Li, Haifeng Chen
3rd Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI). KDD (2024)
Aneesh Komanduri, Chen Zhao, Feng Chen, Xintao Wu
Causal Diffusion Autoencoders: Toward Counterfactual Generation via Diffusion Probabilistic Models. CoRR (2024)
Aneesh Komanduri, Xintao Wu, Yongkai Wu, Feng Chen
From Identifiable Causal Representations to Controllable Counterfactual Generation: A Survey on Causal Generative Modeling. Trans. Mach. Learn. Res. 2024 (2024)
Chen Zhao, Feng Mi, Xintao Wu, Kai Jiang, Latifur Khan, Feng Chen
Dynamic Environment Responsive Online Meta-Learning with Fairness Awareness. CoRR (2024)
Minh-Hao Van, Alycia N. Carey, Xintao Wu
Robust Influence-based Training Methods for Noisy Brain MRI. CoRR (2024)
Huy Mai, Wen Huang, Wei Du, Xintao Wu
A Robust Classifier under Missing-Not-at-Random Sample Selection Bias. BigData (2023)
Alycia N. Carey, Xintao Wu
The statistical fairness field guide: perspectives from social and formal sciences. AI Ethics 3 (1) (2023)
Huy Mai, Xintao Wu
On Prediction Feature Assignment in the Heckman Selection Model. CoRR (2023)
Minh-Hao Van, Alycia N. Carey, Xintao Wu
HINT: Healthy Influential-Noise based Training to Defend against Data Poisoning Attacks. CoRR (2023)
Alycia N. Carey, Karuna Bhaila, Xintao Wu
Randomized Response Has No Disparate Impact on Model Accuracy. BigData (2023)
Chen Zhao, Kai Jiang, Xintao Wu, Haoliang Wang, Latifur Khan, Christan Grant, Feng Chen
Fairness-Aware Domain Generalization under Covariate and Dependence Shifts. CoRR (2023)
Huy Mai, Wen Huang, Wei Du, Xintao Wu
A Robust Classifier Under Missing-Not-At-Random Sample Selection Bias. CoRR (2023)
Minh-Hao Van, Alycia N. Carey, Xintao Wu
HINT: Healthy Influential-Noise based Training to Defend against Data Poisoning Attacks. ICDM (2023)
Minh-Hao Van, Xintao Wu
Detecting and Correcting Hate Speech in Multimodal Memes with Large Visual Language Model. CoRR (2023)
Karuna Bhaila, Wen Huang, Yongkai Wu, Xintao Wu
Local Differential Privacy in Graph Neural Networks: a Reconstruction Approach. CoRR (2023)
Vinay M. S., Shuhan Yuan, Xintao Wu
Robust Fraud Detection via Supervised Contrastive Learning. CoRR (2023)
Chen Zhao, Feng Chen, Xintao Wu, Haifeng Chen, Jiayu Zhou
2nd Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI). KDD (2023)
Chen Zhao, Feng Mi, Xintao Wu, Kai Jiang, Latifur Khan, Christan Grant, Feng Chen
Towards Fair Disentangled Online Learning for Changing Environments. CoRR (2023)
Wen Huang, Xintao Wu
Robustly Improving Bandit Algorithms with Confounded and Selection Biased Offline Data: A Causal Approach. CoRR (2023)
Aneesh Komanduri, Xintao Wu, Yongkai Wu, Feng Chen
From Identifiable Causal Representations to Controllable Counterfactual Generation: A Survey on Causal Generative Modeling. CoRR (2023)
Ethan Prihar, Aaron Haim, Tracy Jia Shen, Adam Sales, Dongwon Lee, Xintao Wu, Neil T. Heffernan
Investigating the Impact of Skill-Related Videos on Online Learning. L@S (2023)
Alycia N. Carey, Minh-Hao Van, Xintao Wu
Evaluating the Impact of Local Differential Privacy on Utility Loss via Influence Functions. CoRR (2023)
Aneesh Komanduri, Yongkai Wu, Feng Chen, Xintao Wu
Learning Causally Disentangled Representations via the Principle of Independent Causal Mechanisms. CoRR (2023)
M. S. Vinay, Shuhan Yuan, Xintao Wu
Robust Fraud Detection via Supervised Contrastive Learning. BigData (2023)
Chen Zhao, Feng Mi, Xintao Wu, Kai Jiang, Latifur Khan, Christan Grant, Feng Chen
Towards Fair Disentangled Online Learning for Changing Environments. KDD (2023)
Wen Huang, Jingbo Zhou, Xintao Wu, Dejing Dou
Mitigating Confounding and Selection Biases in Personalized Recommendation: A Causal Approach. BigData (2023)
Wei Du, Xintao Wu, Hanghang Tong
Fair Regression under Sample Selection Bias. Big Data (2022)
Alycia N. Carey, Xintao Wu
The Causal Fairness Field Guide: Perspectives From Social and Formal Sciences. Frontiers Big Data 5 (2022)
Xiao Han, Depeng Xu, Shuhan Yuan, Xintao Wu
Few-shot Anomaly Detection and Classification Through Reinforced Data Selection. ICDM (2022)
Khang Tran, Phung Lai, NhatHai Phan, Issa Khalil, Yao Ma, Abdallah Khreishah, My Tra Thai, Xintao Wu
Heterogeneous Randomized Response for Differential Privacy in Graph Neural Networks. CoRR (2022)
Vinay M. S., Shuhan Yuan, Xintao Wu
Fraud Detection via Contrastive Positive Unlabeled Learning. Big Data (2022)
Jie Wang, Xintao Wu, Gang Hou, Pengfei Li, Ao Gao, Zhichao Chen, Haoyu Gao
Modeling and reliability verification of industrial control network protocol based on time state transition matrix. Int. J. Commun. Syst. 35 (9) (2022)
Shuhan Yuan, Xintao Wu
Trustworthy Anomaly Detection: A Survey. CoRR (2022)
Alycia N. Carey, Xintao Wu
The Fairness Field Guide: Perspectives from Social and Formal Sciences. CoRR (2022)
Chen Zhao, Feng Mi, Xintao Wu, Kai Jiang, Latifur Khan, Feng Chen
Adaptive Fairness-Aware Online Meta-Learning for Changing Environments. CoRR (2022)
Minh-Hao Van, Wei Du, Xintao Wu, Aidong Lu
Poisoning Attacks on Fair Machine Learning. DASFAA (1) (2022)
Minh-Hao Van, Wei Du, Xintao Wu, Feng Chen, Aidong Lu
Defending Evasion Attacks via Adversarially Adaptive Training. Big Data (2022)
Alycia N. Carey, Wei Du, Xintao Wu
Robust Personalized Federated Learning under Demographic Fairness Heterogeneity. Big Data (2022)
Jian Kang, Tiankai Xie, Xintao Wu, Ross Maciejewski, Hanghang Tong
InfoFair: Information-Theoretic Intersectional Fairness. Big Data (2022)
M. S. Vinay, Shuhan Yuan, Xintao Wu
Contrastive Learning for Insider Threat Detection. DASFAA (1) (2022)
Wen Huang, Lu Zhang, Xintao Wu
Achieving Counterfactual Fairness for Causal Bandit. AAAI (2022)
Aneesh Komanduri, Yongkai Wu, Wen Huang, Feng Chen, Xintao Wu
SCM-VAE: Learning Identifiable Causal Representations via Structural Knowledge. Big Data (2022)
He Cheng, Depeng Xu, Shuhan Yuan, Xintao Wu
Fine-grained Anomaly Detection in Sequential Data via Counterfactual Explanations. CoRR (2022)
Khang Tran, Phung Lai, NhatHai Phan, Issa Khalil, Yao Ma, Abdallah Khreishah, My T. Thai, Xintao Wu
Heterogeneous Randomized Response for Differential Privacy in Graph Neural Networks. Big Data (2022)
Chen Zhao, Feng Chen, Xintao Wu, Christopher Funk, Anthony Hoogs
1st ACM SIGKDD Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI-KDD22). KDD (2022)
Wen Huang, Kevin Labille, Xintao Wu, Dongwon Lee, Neil T. Heffernan
Achieving User-Side Fairness in Contextual Bandits. Hum. Centric Intell. Syst. 2 (3-4) (2022)
Chen Zhao, Feng Mi, Xintao Wu, Kai Jiang, Latifur Khan, Feng Chen
Adaptive Fairness-Aware Online Meta-Learning for Changing Environments. KDD (2022)
Depeng Xu, Shuhan Yuan, Yueyang Wang, Angela Uchechukwu Nwude, Lu Zhang, Anna Zajicek, Xintao Wu
Coded Hate Speech Detection via Contextual Information. PAKDD (1) (2022)
Phung Lai, NhatHai Phan, Abdallah Khreishah, Issa Khalil, Xintao Wu
Model Transferring Attacks to Backdoor HyperNetwork in Personalized Federated Learning. CoRR (2022)
Karuna Bhaila, Yongkai Wu, Xintao Wu
Fair Collective Classification in Networked Data. Big Data (2022)
Wei Du, Xintao Wu
Enhancing personalized modeling via weighted and adversarial learning. Int. J. Data Sci. Anal. 12 (1) (2021)
Minh-Hao Van, Wei Du, Xintao Wu, Aidong Lu
Poisoning Attacks on Fair Machine Learning. CoRR (2021)
Yaowei Hu, Yongkai Wu, Lu Zhang, Xintao Wu
A Generative Adversarial Framework for Bounding Confounded Causal Effects. AAAI (2021)
Shuhan Yuan, Xintao Wu
Deep learning for insider threat detection: Review, challenges and opportunities. Comput. Secur. 104 (2021)
Yebo Feng, Jun Li, Lei Jiao, Xintao Wu
Towards Learning-Based, Content-Agnostic Detection of Social Bot Traffic. IEEE Trans. Dependable Secur. Comput. 18 (5) (2021)
Wen Huang, Kevin Labille, Xintao Wu, Dongwon Lee, Neil Heffernan
Fairness-aware Bandit-based Recommendation. IEEE BigData (2021)
Chenyi Hu, Victor S. Sheng, Ningning Wu, Xintao Wu
Managing Uncertainty in Crowdsourcing with Interval-Valued Labels. NAFIPS (2021)
Haixuan Guo, Shuhan Yuan, Xintao Wu
LogBERT: Log Anomaly Detection via BERT. IJCNN (2021)
Qinghai Zhou, Liangyue Li, Xintao Wu, Nan Cao, Lei Ying, Hanghang Tong
Attent: Active Attributed Network Alignment. WWW (2021)
Wei Du, Xintao Wu, Hanghang Tong
Fair Regression under Sample Selection Bias. CoRR (2021)
Kevin Labille, Wen Huang, Xintao Wu
Transferable Contextual Bandits with Prior Observations. PAKDD (2) (2021)
Wei Du, Depeng Xu, Xintao Wu, Hanghang Tong
Fairness-aware Agnostic Federated Learning. SDM (2021)
Depeng Xu, Wei Du, Xintao Wu
Removing Disparate Impact on Model Accuracy in Differentially Private Stochastic Gradient Descent. KDD (2021)
Wei Du, Xintao Wu
Fair and Robust Classification Under Sample Selection Bias. CIKM (2021)
Jia Tracy Shen, Michiharu Yamashita, Ethan Prihar, Neil Heffernan, Xintao Wu, Dongwon Lee
MathBERT: A Pre-trained Language Model for General NLP Tasks in Mathematics Education. CoRR (2021)
Jia Tracy Shen, Michiharu Yamashita, Ethan Prihar, Neil Heffernan, Xintao Wu, Sean McGrew, Dongwon Lee
Classifying Math Knowledge Components via Task-Adaptive Pre-Trained BERT. AIED (1) (2021)
Jian Kang, Tiankai Xie, Xintao Wu, Ross Maciejewski, Hanghang Tong
MultiFair: Multi-Group Fairness in Machine Learning. CoRR (2021)
Jie Wang, Zhichao Chen, Gang Hou, Haoyu Gao, Pengfei Li, Ao Gao, Xintao Wu
A Modeling and Verification Method of Modbus TCP/IP Protocol. ICA3PP (3) (2021)
Panpan Zheng, Shuhan Yuan, Xintao Wu, Yubao Wu
Hidden Buyer Identification in Darknet Markets via Dirichlet Hawkes Process. IEEE BigData (2021)
Wei Du, Xintao Wu
Robust Fairness-aware Learning Under Sample Selection Bias. CoRR (2021)
Wen Huang, Lu Zhang, Xintao Wu
Achieving Counterfactual Fairness for Causal Bandit. CoRR (2021)
Depeng Xu, Shuhan Yuan, Xintao Wu
Achieving Differential Privacy in Vertically Partitioned Multiparty Learning. IEEE BigData (2021)
Haixuan Guo, Shuhan Yuan, Xintao Wu
LogBERT: Log Anomaly Detection via BERT. CoRR (2021)
Jia Tracy Shen, Michiharu Yamashita, Ethan Prihar, Neil Heffernan, Xintao Wu, Sean McGrew, Dongwon Lee
Classifying Math KCs via Task-Adaptive Pre-Trained BERT. CoRR (2021)
Donghui Hu, Chunya Hu, Yuqi Fan, Xintao Wu
oGBAC - A Group Based Access Control Framework for Information Sharing in Online Social Networks. IEEE Trans. Dependable Secur. Comput. 18 (1) (2021)
Shuhan Yuan, Panpan Zheng, Xintao Wu, Hanghang Tong
Few-shot Insider Threat Detection. CIKM (2020)
Shuhan Yuan, Xintao Wu
Deep Learning for Insider Threat Detection: Review, Challenges and Opportunities. CoRR (2020)
Wen Huang, Yongkai Wu, Xintao Wu
Multi-cause Discrimination Analysis Using Potential Outcomes. SBP-BRiMS (2020)
Yaowei Hu, Yongkai Wu, Lu Zhang, Xintao Wu
Fair Multiple Decision Making Through Soft Interventions. NeurIPS (2020)
Wen Huang, Yongkai Wu, Lu Zhang, Xintao Wu
Fairness through Equality of Effort. WWW (Companion Volume) (2020)
Shudi Shao, Zhengyi Qiu, Xiao Yu, Wei Yang, Guoliang Jin, Tao Xie, Xintao Wu
Database-Access Performance Antipatterns in Database-Backed Web Applications. ICSME (2020)
Wei Du, Xintao Wu
AdvPL: Adversarial Personalized Learning. DSAA (2020)
Depeng Xu, Wei Du, Xintao Wu
Removing Disparate Impact of Differentially Private Stochastic Gradient Descent on Model Accuracy. CoRR (2020)
Wei Du, Depeng Xu, Xintao Wu, Hanghang Tong
Fairness-aware Agnostic Federated Learning. CoRR (2020)
Wen Huang, Kevin Labille, Xintao Wu, Dongwon Lee, Neil Heffernan
Achieving User-Side Fairness in Contextual Bandits. CoRR (2020)
Depeng Xu, Shuhan Yuan, Xintao Wu
Achieving Differential Privacy in Vertically Partitioned Multiparty Learning. CoRR (2019)

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Publication Activity (10 Years)

Top Topics

Top Venues

Xintao Wu