Stop the war!Остановите войну!
for scientists:
default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDXintao Wu
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2022
[j40]Alycia N. Carey
, Xintao Wu:
The Causal Fairness Field Guide: Perspectives From Social and Formal Sciences. Frontiers Big Data 5: 892837 (2022)- [j39]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) - [c118]Wen Huang, Lu Zhang, Xintao Wu:
Achieving Counterfactual Fairness for Causal Bandit. AAAI 2022: 6952-6959 - [c117]Minh-Hao Van, Wei Du, Xintao Wu, Aidong Lu:
Poisoning Attacks on Fair Machine Learning. DASFAA (1) 2022: 370-386 - [c116]M. S. Vinay, Shuhan Yuan, Xintao Wu:
Contrastive Learning for Insider Threat Detection. DASFAA (1) 2022: 395-403 - [c115]Xiao Han, Depeng Xu, Shuhan Yuan, Xintao Wu:
Few-shot Anomaly Detection and Classification Through Reinforced Data Selection. ICDM 2022: 963-968 - [c114]Chen Zhao, Feng Mi, Xintao Wu, Kai Jiang, Latifur Khan, Feng Chen:
Adaptive Fairness-Aware Online Meta-Learning for Changing Environments. KDD 2022: 2565-2575 - [c113]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: 4914-4915 - [c112]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: 93-105 - [i40]Alycia N. Carey, Xintao Wu:
The Fairness Field Guide: Perspectives from Social and Formal Sciences. CoRR abs/2201.05216 (2022) - [i39]Phung Lai, NhatHai Phan, Abdallah Khreishah, Issa Khalil, Xintao Wu:
Model Transferring Attacks to Backdoor HyperNetwork in Personalized Federated Learning. CoRR abs/2201.07063 (2022) - [i38]Shuhan Yuan, Xintao Wu:
Trustworthy Anomaly Detection: A Survey. CoRR abs/2202.07787 (2022) - [i37]Chen Zhao, Feng Mi, Xintao Wu, Kai Jiang, Latifur Khan, Feng Chen:
Adaptive Fairness-Aware Online Meta-Learning for Changing Environments. CoRR abs/2205.11264 (2022) - [i36]He Cheng, Depeng Xu, Shuhan Yuan, Xintao Wu:
Fine-grained Anomaly Detection in Sequential Data via Counterfactual Explanations. CoRR abs/2210.04145 (2022) - [i35]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 abs/2211.05766 (2022) - 2021
- [j38]Shuhan Yuan, Xintao Wu:
Deep learning for insider threat detection: Review, challenges and opportunities. Comput. Secur. 104: 102221 (2021) - [j37]Wei Du, Xintao Wu:
Enhancing personalized modeling via weighted and adversarial learning. Int. J. Data Sci. Anal. 12(1): 1-14 (2021) - [j36]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): 100-116 (2021) - [j35]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): 2149-2163 (2021) - [c111]Yaowei Hu, Yongkai Wu, Lu Zhang, Xintao Wu:
A Generative Adversarial Framework for Bounding Confounded Causal Effects. AAAI 2021: 12104-12112 - [c110]Jia Tracy Shen, Michiharu Yamashita, Ethan Prihar, Neil T. Heffernan, Xintao Wu, Sean McGrew, Dongwon Lee:
Classifying Math Knowledge Components via Task-Adaptive Pre-Trained BERT. AIED (1) 2021: 408-419 - [c109]Panpan Zheng, Shuhan Yuan, Xintao Wu, Yubao Wu:
Hidden Buyer Identification in Darknet Markets via Dirichlet Hawkes Process. IEEE BigData 2021: 581-589 - [c108]Wen Huang, Kevin Labille, Xintao Wu, Dongwon Lee, Neil T. Heffernan:
Fairness-aware Bandit-based Recommendation. IEEE BigData 2021: 1273-1278 - [c107]Depeng Xu, Shuhan Yuan, Xintao Wu:
Achieving Differential Privacy in Vertically Partitioned Multiparty Learning. IEEE BigData 2021: 5474-5483 - [c106]Wei Du, Xintao Wu:
Fair and Robust Classification Under Sample Selection Bias. CIKM 2021: 2999-3003 - [c105]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: 527-539 - [c104]Haixuan Guo, Shuhan Yuan, Xintao Wu:
LogBERT: Log Anomaly Detection via BERT. IJCNN 2021: 1-8 - [c103]Depeng Xu, Wei Du, Xintao Wu:
Removing Disparate Impact on Model Accuracy in Differentially Private Stochastic Gradient Descent. KDD 2021: 1924-1932 - [c102]Chenyi Hu, Victor S. Sheng, Ningning Wu, Xintao Wu:
Managing Uncertainty in Crowdsourcing with Interval-Valued Labels. NAFIPS 2021: 166-178 - [c101]Kevin Labille, Wen Huang, Xintao Wu:
Transferable Contextual Bandits with Prior Observations. PAKDD (2) 2021: 398-410 - [c100]Wei Du, Depeng Xu, Xintao Wu, Hanghang Tong:
Fairness-aware Agnostic Federated Learning. SDM 2021: 181-189 - [c99]Qinghai Zhou, Liangyue Li, Xintao Wu, Nan Cao, Lei Ying, Hanghang Tong:
Attent: Active Attributed Network Alignment. WWW 2021: 3896-3906 - [i34]Haixuan Guo, Shuhan Yuan, Xintao Wu:
LogBERT: Log Anomaly Detection via BERT. CoRR abs/2103.04475 (2021) - [i33]Jian Kang, Tiankai Xie, Xintao Wu, Ross Maciejewski, Hanghang Tong:
MultiFair: Multi-Group Fairness in Machine Learning. CoRR abs/2105.11069 (2021) - [i32]Jia Tracy Shen, Michiharu Yamashita, Ethan Prihar, Neil T. Heffernan, Xintao Wu, Sean McGrew, Dongwon Lee:
Classifying Math KCs via Task-Adaptive Pre-Trained BERT. CoRR abs/2105.11343 (2021) - [i31]Wei Du, Xintao Wu:
Robust Fairness-aware Learning Under Sample Selection Bias. CoRR abs/2105.11570 (2021) - [i30]Jia Tracy Shen, Michiharu Yamashita, Ethan Prihar, Neil T. Heffernan, Xintao Wu, Dongwon Lee:
MathBERT: A Pre-trained Language Model for General NLP Tasks in Mathematics Education. CoRR abs/2106.07340 (2021) - [i29]Wen Huang, Lu Zhang, Xintao Wu:
Achieving Counterfactual Fairness for Causal Bandit. CoRR abs/2109.10458 (2021) - [i28]Wei Du, Xintao Wu, Hanghang Tong:
Fair Regression under Sample Selection Bias. CoRR abs/2110.04372 (2021) - [i27]Minh-Hao Van, Wei Du, Xintao Wu, Aidong Lu:
Poisoning Attacks on Fair Machine Learning. CoRR abs/2110.08932 (2021) - 2020
- [c98]Shuhan Yuan, Panpan Zheng, Xintao Wu, Hanghang Tong:
Few-shot Insider Threat Detection. CIKM 2020: 2289-2292 - [c97]Wei Du, Xintao Wu:
AdvPL: Adversarial Personalized Learning. DSAA 2020: 90-98 - [c96]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: 58-69 - [c95]Yaowei Hu, Yongkai Wu, Lu Zhang, Xintao Wu:
Fair Multiple Decision Making Through Soft Interventions. NeurIPS 2020 - [c94]Wen Huang, Yongkai Wu, Xintao Wu:
Multi-cause Discrimination Analysis Using Potential Outcomes. SBP-BRiMS 2020: 224-234 - [c93]Wen Huang, Yongkai Wu, Lu Zhang, Xintao Wu:
Fairness through Equality of Effort. WWW (Companion Volume) 2020: 743-751 - [e1]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 IEEE International Conference on Big Data (IEEE BigData 2020), Atlanta, GA, USA, December 10-13, 2020. IEEE 2020, ISBN 978-1-7281-6251-5 [contents] - [i26]Depeng Xu, Wei Du, Xintao Wu:
Removing Disparate Impact of Differentially Private Stochastic Gradient Descent on Model Accuracy. CoRR abs/2003.03699 (2020) - [i25]Shuhan Yuan, Xintao Wu:
Deep Learning for Insider Threat Detection: Review, Challenges and Opportunities. CoRR abs/2005.12433 (2020) - [i24]Wei Du, Depeng Xu, Xintao Wu, Hanghang Tong:
Fairness-aware Agnostic Federated Learning. CoRR abs/2010.05057 (2020) - [i23]Wen Huang, Kevin Labille, Xintao Wu, Dongwon Lee, Neil T. Heffernan:
Achieving User-Side Fairness in Contextual Bandits. CoRR abs/2010.12102 (2020)
2010 – 2019
- 2019
- [j34]Lu Zhang, Qiuping Pan, Yue Wang, Xintao Wu, Xinghua Shi:
Bayesian Network Construction and Genotype-Phenotype Inference Using GWAS Statistics. IEEE ACM Trans. Comput. Biol. Bioinform. 16(2): 475-489 (2019) - [j33]Lu Zhang, Yongkai Wu, Xintao Wu:
Causal Modeling-Based Discrimination Discovery and Removal: Criteria, Bounds, and Algorithms. IEEE Trans. Knowl. Data Eng. 31(11): 2035-2050 (2019) - [c92]Panpan Zheng, Shuhan Yuan, Xintao Wu:
SAFE: A Neural Survival Analysis Model for Fraud Early Detection. AAAI 2019: 1278-1285 - [c91]Panpan Zheng, Shuhan Yuan, Xintao Wu, Jun Li, Aidong Lu:
One-Class Adversarial Nets for Fraud Detection. AAAI 2019: 1286-1293 - [c90]Shuhan Yuan, Panpan Zheng, Xintao Wu, Qinghua Li:
Insider Threat Detection via Hierarchical Neural Temporal Point Processes. IEEE BigData 2019: 1343-1350 - [c89]Depeng Xu, Shuhan Yuan, Lu Zhang, Xintao Wu:
FairGAN+: Achieving Fair Data Generation and Classification through Generative Adversarial Nets. IEEE BigData 2019: 1401-1406 - [c88]Yebo Feng, Jun Li, Lei Jiao, Xintao Wu:
BotFlowMon: Learning-based, Content-Agnostic Identification of Social Bot Traffic Flows. CNS 2019: 169-177 - [c87]Yongkai Wu, Lu Zhang, Xintao Wu:
Counterfactual Fairness: Unidentification, Bound and Algorithm. IJCAI 2019: 1438-1444 - [c86]Depeng Xu, Yongkai Wu, Shuhan Yuan, Lu Zhang, Xintao Wu:
Achieving Causal Fairness through Generative Adversarial Networks. IJCAI 2019: 1452-1458 - [c85]NhatHai Phan, Minh N. Vu, Yang Liu, Ruoming Jin, Dejing Dou, Xintao Wu, My T. Thai:
Heterogeneous Gaussian Mechanism: Preserving Differential Privacy in Deep Learning with Provable Robustness. IJCAI 2019: 4753-4759 - [c84]Yongkai Wu, Lu Zhang, Xintao Wu, Hanghang Tong:
PC-Fairness: A Unified Framework for Measuring Causality-based Fairness. NeurIPS 2019: 3399-3409 - [c83]Yuemeng Li, Aidong Lu, Xintao Wu, Shuhan Yuan:
Dynamic Anomaly Detection Using Vector Autoregressive Model. PAKDD (1) 2019: 600-611 - [c82]Xucan Chen, Mohammad Al Hasan, Xintao Wu, Pavel Skums, Mohammad Javad Feizollahi, Marie Ouellet, Eric L. Sevigny, David Maimon, Yubao Wu:
Characteristics of Bitcoin Transactions on Cryptomarkets. SpaCCS 2019: 261-276 - [c81]Depeng Xu, Shuhan Yuan, Xintao Wu:
Achieving Differential Privacy and Fairness in Logistic Regression. WWW (Companion Volume) 2019: 594-599 - [c80]Yongkai Wu, Lu Zhang, Xintao Wu:
On Convexity and Bounds of Fairness-aware Classification. WWW 2019: 3356-3362 - [i22]NhatHai Phan, Minh N. Vu, Yang Liu, Ruoming Jin, Dejing Dou, Xintao Wu, My T. Thai:
Heterogeneous Gaussian Mechanism: Preserving Differential Privacy in Deep Learning with Provable Robustness. CoRR abs/1906.01444 (2019) - [i21]Shuhan Yuan, Panpan Zheng, Xintao Wu, Qinghua Li:
Insider Threat Detection via Hierarchical Neural Temporal Point Processes. CoRR abs/1910.03171 (2019) - [i20]Yongkai Wu, Lu Zhang, Xintao Wu, Hanghang Tong:
PC-Fairness: A Unified Framework for Measuring Causality-based Fairness. CoRR abs/1910.12586 (2019) - [i19]Depeng Xu, Shuhan Yuan, Xintao Wu:
Achieving Differential Privacy in Vertically Partitioned Multiparty Learning. CoRR abs/1911.04587 (2019) - [i18]Panpan Zheng, Shuhan Yuan, Xintao Wu, Yubao Wu:
Identifying Hidden Buyers in Darknet Markets via Dirichlet Hawkes Process. CoRR abs/1911.04620 (2019) - [i17]Wen Huang, Yongkai Wu, Lu Zhang, Xintao Wu:
Fairness through Equality of Effort. CoRR abs/1911.08292 (2019) - 2018
- [j32]Shuhan Yuan, Xintao Wu, Yang Xiang:
Task-specific word identification from short texts using a convolutional neural network. Intell. Data Anal. 22(3): 533-550 (2018) - [j31]Yuemeng Li, Shuhan Yuan, Xintao Wu, Aidong Lu:
On spectral analysis of directed signed graphs. Int. J. Data Sci. Anal. 6(2): 147-162 (2018) - [j30]Shuhan Yuan, Xintao Wu, Yang Xiang:
Incorporating pre-training in long short-term memory networks for tweet classification. Soc. Netw. Anal. Min. 8(1): 52:1-52:16 (2018) - [c79]Depeng Xu, Shuhan Yuan, Lu Zhang, Xintao Wu:
FairGAN: Fairness-aware Generative Adversarial Networks. IEEE BigData 2018: 570-575 - [c78]Lu Zhang, Yongkai Wu, Xintao Wu:
Achieving Non-Discrimination in Prediction. IJCAI 2018: 3097-3103 - [c77]Yongkai Wu, Lu Zhang, Xintao Wu:
On Discrimination Discovery and Removal in Ranked Data using Causal Graph. KDD 2018: 2536-2544 - [c76]Depeng Xu, Shuhan Yuan, Xintao Wu, NhatHai Phan:
DPNE: Differentially Private Network Embedding. PAKDD (2) 2018: 235-246 - [i16]Panpan Zheng, Shuhan Yuan, Xintao Wu, Jun Li, Aidong Lu:
One-Class Adversarial Nets for Fraud Detection. CoRR abs/1803.01798 (2018) - [i15]Yongkai Wu, Lu Zhang, Xintao Wu:
On Discrimination Discovery and Removal in Ranked Data using Causal Graph. CoRR abs/1803.01901 (2018) - [i14]Depeng Xu, Shuhan Yuan, Lu Zhang, Xintao Wu:
FairGAN: Fairness-aware Generative Adversarial Networks. CoRR abs/1805.11202 (2018) - [i13]Panpan Zheng, Shuhan Yuan, Xintao Wu:
SAFE: A Neural Survival Analysis Model for Fraud Early Detection. CoRR abs/1809.04683 (2018) - [i12]Yongkai Wu, Lu Zhang, Xintao Wu:
Fairness-aware Classification: Criterion, Convexity, and Bounds. CoRR abs/1809.04737 (2018) - 2017
- [j29]Lu Zhang, Xintao Wu:
Anti-discrimination learning: a causal modeling-based framework. Int. J. Data Sci. Anal. 4(1): 1-16 (2017) - [j28]NhatHai Phan, Xintao Wu, Dejing Dou:
Preserving differential privacy in convolutional deep belief networks. Mach. Learn. 106(9-10): 1681-1704 (2017) - [j27]Leting Wu, Xintao Wu, Aidong Lu, Yuemeng Li:
On Spectral Analysis of Signed and Dispute Graphs: Application to Community Structure. IEEE Trans. Knowl. Data Eng. 29(7): 1480-1493 (2017) - [c75]Lu Zhang, Qiuping Pan, Xintao Wu:
Modeling SNP and quantitative trait association from GWAS catalog using CLG Bayesian network. BIBM 2017: 266-269 - [c74]Qiuping Pan, Lu Zhang, Xintao Wu:
STIP: An SNP-trait inference platform. BIBM 2017: 915-920 - [c73]Shuhan Yuan, Xintao Wu, Jun Li, Aidong Lu:
Spectrum-based Deep Neural Networks for Fraud Detection. CIKM 2017: 2419-2422 - [c72]Yuemeng Li, Xintao Wu, Aidong Lu:
On Spectral Analysis of Directed Signed Graphs. DSAA 2017: 539-548 - [c71]NhatHai Phan, Xintao Wu, Han Hu, Dejing Dou:
Adaptive Laplace Mechanism: Differential Privacy Preservation in Deep Learning. ICDM 2017: 385-394 - [c70]Lu Zhang, Yongkai Wu, Xintao Wu:
A Causal Framework for Discovering and Removing Direct and Indirect Discrimination. IJCAI 2017: 3929-3935 - [c69]Lu Zhang, Yongkai Wu, Xintao Wu:
Achieving Non-Discrimination in Data Release. KDD 2017: 1335-1344 - [c68]Depeng Xu, Shuhan Yuan, Xintao Wu:
Differential Privacy Preserving Causal Graph Discovery. PAC 2017: 60-71 - [c67]Srinidhi Katla, Depeng Xu, Yongkai Wu, Qiuping Pan, Xintao Wu:
DPWeka: Achieving Differential Privacy in WEKA. PAC 2017: 184-185 - [c66]Shuhan Yuan, Xintao Wu, Yang Xiang:
SNE: Signed Network Embedding. PAKDD (2) 2017: 183-195 - [c65]Shuhan Yuan, Panpan Zheng, Xintao Wu, Yang Xiang:
Wikipedia Vandal Early Detection: From User Behavior to User Embedding. ECML/PKDD (1) 2017: 832-846 - [i11]Lu Zhang, Yongkai Wu, Xintao Wu:
Achieving non-discrimination in prediction. CoRR abs/1703.00060 (2017) - [i10]Shuhan Yuan, Xintao Wu, Yang Xiang:
SNE: Signed Network Embedding. CoRR abs/1703.04837 (2017) - [i9]Shuhan Yuan, Xintao Wu, Yang Xiang:
Task-specific Word Identification from Short Texts Using a Convolutional Neural Network. CoRR abs/1706.00884 (2017) - [i8]Shuhan Yuan, Panpan Zheng, Xintao Wu, Yang Xiang:
Wikipedia Vandal Early Detection: from User Behavior to User Embedding. CoRR abs/1706.00887 (2017) - [i7]Shuhan Yuan, Xintao Wu, Jun Li, Aidong Lu:
Spectrum-based deep neural networks for fraud detection. CoRR abs/1706.00891 (2017) - [i6]NhatHai Phan, Xintao Wu, Dejing Dou:
Preserving Differential Privacy in Convolutional Deep Belief Networks. CoRR abs/1706.08839 (2017) - [i5]NhatHai Phan, Xintao Wu, Han Hu, Dejing Dou:
Adaptive Laplace Mechanism: Differential Privacy Preservation in Deep Learning. CoRR abs/1709.05750 (2017) - 2016
- [j26]Donghui Hu, Xiaotian Zhang, Yuqi Fan, Zhong-Qiu Zhao, Lina Wang, Xintao Wu, Xindong Wu:
On digital image trustworthiness. Appl. Soft Comput. 48: 240-253 (2016) - [c64]NhatHai Phan, Yue Wang, Xintao Wu, Dejing Dou:
Differential Privacy Preservation for Deep Auto-Encoders: an Application of Human Behavior Prediction. AAAI 2016: 1309-1316 - [c63]Yuemeng Li, Xintao Wu, Song Yang:
Social network dominance based on analysis of asymmetry. ASONAM 2016: 146-151 - [c62]Lu Zhang, Qiuping Pan, Xintao Wu, Xinghua Shi:
Building Bayesian networks from GWAS statistics based on Independence of Causal Influence. BIBM 2016: 529-532 - [c61]Yue Wang, Jia Wen, Xintao Wu, Xinghua Shi:
Infringement of Individual Privacy via Mining Differentially Private GWAS Statistics. BigCom 2016: 355-366 - [c60]Yongkai Wu, Xintao Wu:
Using Loglinear Model for Discrimination Discovery and Prevention. DSAA 2016: 110-119 - [c59]Donghui Hu, Fan Chen, Xintao Wu, Zhong-Qiu Zhao:
A Framework of Privacy Decision Recommendation for Image Sharing in Online Social Networks. DSC 2016: 243-251 - [c58]Yue Wang, Xintao Wu, Donghui Hu:
Using Randomized Response for Differential Privacy Preserving Data Collection. EDBT/ICDT Workshops 2016 - [c57]Shuhan Yuan, Xintao Wu, Yang Xiang:
A Two Phase Deep Learning Model for Identifying Discrimination from Tweets. EDBT 2016: 696-697 - [c56]Shuhan Yuan, Xintao Wu, Yang Xiang:
Incorporating Pre-Training in Long Short-Term Memory Networks for Tweets Classification. ICDM 2016: 1329-1334 - [c55]Lu Zhang, Yongkai Wu, Xintao Wu:
Situation Testing-Based Discrimination Discovery: A Causal Inference Approach. IJCAI 2016: 2718-2724 - [c54]Lu Zhang, Yongkai Wu, Xintao Wu:
On Discrimination Discovery Using Causal Networks. SBP-BRiMS 2016: 83-93 - [i4]Lu Zhang, Yongkai Wu, Xintao Wu:
Achieving non-discrimination in data release. CoRR abs/1611.07438 (2016) - [i3]