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2020 – today
- 2024
[j46]Weina Zhou
, Hong Wang, Xintao Wu:
WSA-YOLOv5s: improved YOLOv5s based on window self-attention module for ship detection. Pattern Anal. Appl. 27(4): 126 (2024)- [j45]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): 153:1-153:23 (2024) - [j44]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) - [c148]Wen Huang, Xintao Wu:
Robustly Improving Bandit Algorithms with Confounded and Selection Biased Offline Data: A Causal Approach. AAAI 2024: 20438-20446 - [c147]Minh-Hao Van, Prateek Verma, Xintao Wu:
On Large Visual Language Models for Medical Imaging Analysis: An Empirical Study. CHASE 2024: 172-176 - [c146]Aneesh Komanduri, Chen Zhao, Feng Chen, Xintao Wu:
Causal Diffusion Autoencoders: Toward Counterfactual Generation via Diffusion Probabilistic Models. ECAI 2024: 2516-2523 - [c145]Vinay M. S., Shuhan Yuan, Xintao Wu:
Contrastive Learning for Fraud Detection from Noisy Labels. ICDE 2024: 1421-1434 - [c144]Aneesh Komanduri, Yongkai Wu, Feng Chen, Xintao Wu:
Learning Causally Disentangled Representations via the Principle of Independent Causal Mechanisms. IJCAI 2024: 4308-4316 - [c143]Minglai Shao, Dong Li, Chen Zhao, Xintao Wu, Yujie Lin, Qin Tian:
Supervised Algorithmic Fairness in Distribution Shifts: A Survey. IJCAI 2024: 8225-8233 - [c142]Karuna Bhaila, Xintao Wu:
Cascading Failure Prediction in Power Grid Using Node and Edge Attributed Graph Neural Networks. IJCNN 2024: 1-7 - [c141]Alycia N. Carey, Minh-Hao Van, Xintao Wu:
Evaluating the Impact of Local Differential Privacy on Utility Loss via Influence Functions. IJCNN 2024: 1-10 - [c140]Huy Mai, Xintao Wu:
On Prediction Feature Assignment in the Heckman Selection Model. IJCNN 2024: 1-8 - [c139]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: 4419-4430 - [c138]Chen Zhao, Feng Chen, Xintao Wu, Jundong Li, Haifeng Chen:
3rd Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI). KDD 2024: 6751-6752 - [c137]Minh-Hao Van, Alycia N. Carey, Xintao Wu:
Robust Influence-Based Training Methods for Noisy Brain MRI. PKDD (4) 2024: 246-257 - [c136]He Cheng, Depeng Xu, Shuhan Yuan, Xintao Wu:
Achieving Counterfactual Explanation for Sequence Anomaly Detection. ECML/PKDD (8) 2024: 19-35 - [c135]Karuna Bhaila, Wen Huang, Yongkai Wu, Xintao Wu:
Local Differential Privacy in Graph Neural Networks: a Reconstruction Approach. SDM 2024: 1-9 - [i63]Yujie Lin, Dong Li, Chen Zhao, Xintao Wu, Qin Tian, Minglai Shao:
Supervised Algorithmic Fairness in Distribution Shifts: A Survey. CoRR abs/2402.01327 (2024) - [i62]Vinay M. S., Minh-Hao Van, Xintao Wu:
In-Context Learning Demonstration Selection via Influence Analysis. CoRR abs/2402.11750 (2024) - [i61]Chen Zhao, Feng Mi, Xintao Wu, Kai Jiang, Latifur Khan, Feng Chen:
Dynamic Environment Responsive Online Meta-Learning with Fairness Awareness. CoRR abs/2402.12319 (2024) - [i60]Minh-Hao Van, Prateek Verma, Xintao Wu:
On Large Visual Language Models for Medical Imaging Analysis: An Empirical Study. CoRR abs/2402.14162 (2024) - [i59]Alycia N. Carey, Karuna Bhaila, Kennedy Edemacu, Xintao Wu:
DP-TabICL: In-Context Learning with Differentially Private Tabular Data. CoRR abs/2403.05681 (2024) - [i58]Minh-Hao Van, Alycia N. Carey, Xintao Wu:
Robust Influence-based Training Methods for Noisy Brain MRI. CoRR abs/2403.10698 (2024) - [i57]Kennedy Edemacu, Xintao Wu:
Privacy Preserving Prompt Engineering: A Survey. CoRR abs/2404.06001 (2024) - [i56]Aneesh Komanduri, Chen Zhao, Feng Chen, Xintao Wu:
Causal Diffusion Autoencoders: Toward Counterfactual Generation via Diffusion Probabilistic Models. CoRR abs/2404.17735 (2024) - [i55]Prateek Verma, Minh-Hao Van, Xintao Wu:
Beyond Human Vision: The Role of Large Vision Language Models in Microscope Image Analysis. CoRR abs/2405.00876 (2024) - [i54]Karuna Bhaila, Minh-Hao Van, Xintao Wu:
Soft Prompting for Unlearning in Large Language Models. CoRR abs/2406.12038 (2024) - [i53]Karuna Bhaila, Minh-Hao Van, Kennedy Edemacu, Chen Zhao, Feng Chen, Xintao Wu:
Fair In-Context Learning via Latent Concept Variables. CoRR abs/2411.02671 (2024) - 2023
- [j43]Alycia N. Carey, Xintao Wu:
The statistical fairness field guide: perspectives from social and formal sciences. AI Ethics 3(1): 1-23 (2023) - [c134]Wen Huang, Jingbo Zhou, Xintao Wu, Dejing Dou:
Mitigating Confounding and Selection Biases in Personalized Recommendation: A Causal Approach. IEEE Big Data 2023: 27-36 - [c133]Huy Mai, Wen Huang, Wei Du, Xintao Wu:
A Robust Classifier under Missing-Not-at-Random Sample Selection Bias. IEEE Big Data 2023: 1206-1213 - [c132]M. S. Vinay, Shuhan Yuan, Xintao Wu:
Robust Fraud Detection via Supervised Contrastive Learning. IEEE Big Data 2023: 1279-1288 - [c131]Alycia N. Carey, Karuna Bhaila, Xintao Wu:
Randomized Response Has No Disparate Impact on Model Accuracy. IEEE Big Data 2023: 5460-5465 - [c130]Minh-Hao Van, Alycia N. Carey, Xintao Wu:
HINT: Healthy Influential-Noise based Training to Defend against Data Poisoning Attacks. ICDM 2023: 608-617 - [c129]Chen Zhao, Feng Mi, Xintao Wu, Kai Jiang, Latifur Khan, Christan Grant, Feng Chen:
Towards Fair Disentangled Online Learning for Changing Environments. KDD 2023: 3480-3491 - [c128]Chen Zhao, Feng Chen, Xintao Wu, Haifeng Chen, Jiayu Zhou:
2nd Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI). KDD 2023: 5903-5904 - [c127]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: 4-13 - [i52]Huy Mai, Wen Huang, Wei Du, Xintao Wu:
A Robust Classifier Under Missing-Not-At-Random Sample Selection Bias. CoRR abs/2305.15641 (2023) - [i51]Chen Zhao, Feng Mi, Xintao Wu, Kai Jiang, Latifur Khan, Christan Grant, Feng Chen:
Towards Fair Disentangled Online Learning for Changing Environments. CoRR abs/2306.01007 (2023) - [i50]Aneesh Komanduri, Yongkai Wu, Feng Chen, Xintao Wu:
Learning Causally Disentangled Representations via the Principle of Independent Causal Mechanisms. CoRR abs/2306.01213 (2023) - [i49]Vinay M. S., Shuhan Yuan, Xintao Wu:
Robust Fraud Detection via Supervised Contrastive Learning. CoRR abs/2308.10055 (2023) - [i48]Huy Mai, Xintao Wu:
On Prediction Feature Assignment in the Heckman Selection Model. CoRR abs/2309.08043 (2023) - [i47]Minh-Hao Van, Alycia N. Carey, Xintao Wu:
HINT: Healthy Influential-Noise based Training to Defend against Data Poisoning Attacks. CoRR abs/2309.08549 (2023) - [i46]Karuna Bhaila, Wen Huang, Yongkai Wu, Xintao Wu:
Local Differential Privacy in Graph Neural Networks: a Reconstruction Approach. CoRR abs/2309.08569 (2023) - [i45]Alycia N. Carey, Minh-Hao Van, Xintao Wu:
Evaluating the Impact of Local Differential Privacy on Utility Loss via Influence Functions. CoRR abs/2309.08678 (2023) - [i44]Aneesh Komanduri, Xintao Wu, Yongkai Wu, Feng Chen:
From Identifiable Causal Representations to Controllable Counterfactual Generation: A Survey on Causal Generative Modeling. CoRR abs/2310.11011 (2023) - [i43]Minh-Hao Van, Xintao Wu:
Detecting and Correcting Hate Speech in Multimodal Memes with Large Visual Language Model. CoRR abs/2311.06737 (2023) - [i42]Chen Zhao, Kai Jiang, Xintao Wu, Haoliang Wang, Latifur Khan, Christan Grant, Feng Chen:
Fairness-Aware Domain Generalization under Covariate and Dependence Shifts. CoRR abs/2311.13816 (2023) - [i41]Wen Huang, Xintao Wu:
Robustly Improving Bandit Algorithms with Confounded and Selection Biased Offline Data: A Causal Approach. CoRR abs/2312.12731 (2023) - 2022
- [j42]Panpan Zheng, Shuhan Yuan, Xintao Wu:
Using Dirichlet Marked Hawkes Processes for Insider Threat Detection. DTRAP 3(1): 5:1-5:19 (2022) - [j41]Alycia N. Carey, Xintao Wu:
The Causal Fairness Field Guide: Perspectives From Social and Formal Sciences. Frontiers Big Data 5: 892837 (2022) - [j40]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): 81-94 (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) - [c126]Wen Huang, Lu Zhang, Xintao Wu:
Achieving Counterfactual Fairness for Causal Bandit. AAAI 2022: 6952-6959 - [c125]Aneesh Komanduri, Yongkai Wu, Wen Huang, Feng Chen, Xintao Wu:
SCM-VAE: Learning Identifiable Causal Representations via Structural Knowledge. IEEE Big Data 2022: 1014-1023 - [c124]Karuna Bhaila, Yongkai Wu, Xintao Wu:
Fair Collective Classification in Networked Data. IEEE Big Data 2022: 1415-1424 - [c123]Alycia N. Carey, Wei Du, Xintao Wu:
Robust Personalized Federated Learning under Demographic Fairness Heterogeneity. IEEE Big Data 2022: 1425-1434 - [c122]Wei Du, Xintao Wu, Hanghang Tong:
Fair Regression under Sample Selection Bias. IEEE Big Data 2022: 1435-1444 - [c121]Jian Kang, Tiankai Xie, Xintao Wu, Ross Maciejewski, Hanghang Tong:
InfoFair: Information-Theoretic Intersectional Fairness. IEEE Big Data 2022: 1455-1464 - [c120]Vinay M. S., Shuhan Yuan, Xintao Wu:
Fraud Detection via Contrastive Positive Unlabeled Learning. IEEE Big Data 2022: 1475-1484 - [c119]Minh-Hao Van, Wei Du, Xintao Wu, Feng Chen, Aidong Lu:
Defending Evasion Attacks via Adversarially Adaptive Training. IEEE Big Data 2022: 1515-1524 - [c118]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. IEEE Big Data 2022: 1582-1587 - [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]Lu Zhang, Yongkai Wu, Xintao Wu:
A causal framework for discovering and removing direct and indirect discrimination. CoRR abs/1611.07509 (2016) - [i2]Yuemeng Li, Xintao Wu, Aidong Lu:
On Spectral Analysis of Directed Signed Graphs. CoRR abs/1612.08102 (2016) - 2015
- [j25]Kai Pan, Xintao Wu, Tao Xie:
Program-input generation for testing database applications using existing database states. Autom. Softw. Eng. 22(4): 439-473 (2015) - [j24]Donghui Hu, Bin Su, Shuli Zheng, Zhong-Qiu Zhao, Xintao Wu, Xindong Wu:
Security and privacy protocols for perceptual image hashing. Int. J. Sens. Networks 17(3): 146-162 (2015) - [j23]Feng Luo, Xintao Wu:
Guest Editorial for Special Section on BIBM 2013. IEEE ACM Trans. Comput. Biol. Bioinform. 12(2): 252-253 (2015) - [j22]Ju-Hua Hu, De-Chuan Zhan, Xintao Wu, Yuan Jiang, Zhi-Hua Zhou:
Pairwised Specific Distance Learning from Physical Linkages. ACM Trans. Knowl. Discov. Data 9(3): 20:1-20:27 (2015) - [c53]Xianlin Hu, Leting Wu, Aidong Lu, Xintao Wu:
Block-Organized Topology Visualization for Visual Exploration of Signed Networks. ICDM Workshops 2015: 652-659 - [c52]Yuemeng Li, Xintao Wu, Aidong Lu:
Analysis of Spectral Space Properties of Directed Graphs Using Matrix Perturbation Theory with Application in Graph Partition. ICDM 2015: 847-852 - [c51]Yue Wang, Cheng Si, Xintao Wu:
Regression Model Fitting under Differential Privacy and Model Inversion Attack. IJCAI 2015: 1003-1009 - [c50]Zhilin Luo, Yue Wang, Xintao Wu, Wandong Cai, Ting Chen:
On Burst Detection and Prediction in Retweeting Sequence. PAKDD (1) 2015: 96-107 - 2014
- [j21]Kai Pan, Xintao Wu, Tao Xie:
Guided test generation for database applications via synthesized database interactions. ACM Trans. Softw. Eng. Methodol. 23(2): 12:1-12:27 (2014) - [c49]Leting Wu, Xintao Wu, Aidong Lu, Yuemeng Li:
On Spectral Analysis of Signed and Dispute Graphs. ICDM 2014: 1049-1054 - 2013
- [j20]Xianlin Hu, Aidong Lu, Xintao Wu:
Spectrum-Based Network Visualization for Topology Analysis. IEEE Computer Graphics and Applications 33(1): 58-68 (2013) - [j19]Leting Wu, Xintao Wu, Aidong Lu, Zhi-Hua Zhou:
A spectral approach to detecting subtle anomalies in graphs. J. Intell. Inf. Syst. 41(2): 313-337 (2013) - [j18]Yue Wang, Xintao Wu, Jun Zhu, Yang Xiang:
On learning cluster coefficient of private networks. Soc. Netw. Anal. Min. 3(4): 925-938 (2013) - [j17]Yue Wang, Xintao Wu:
Preserving Differential Privacy in Degree-Correlation based Graph Generation. Trans. Data Priv. 6(2): 127-145 (2013) - [c48]Yue Wang, Xintao Wu, Xinghua Shi:
Using aggregate human genome data for individual identification. BIBM 2013: 410-415 - [c47]Kai Pan, Xintao Wu, Tao Xie:
Automatic test generation for mutation testing on database applications. AST 2013: 111-117 - [c46]Yue Wang, Xintao Wu, Leting Wu:
Differential Privacy Preserving Spectral Graph Analysis. PAKDD (2) 2013: 329-340 - [c45]Xiaowei Ying, Xintao Wu, Yue Wang:
On Linear Refinement of Differential Privacy-Preserving Query Answering. PAKDD (2) 2013: 353-364 - 2012
- [j16]Leting Wu, Xiaowei Ying, Xintao Wu, Aidong Lu, Zhi-Hua Zhou:
Examining spectral space of complex networks with positive and negative links. Int. J. Soc. Netw. Min. 1(1): 91-111 (2012) - [c44]Zhilin Luo, Xintao Wu, Wandong Cai, Dong Peng:
Examining Multi-factor Interactions in Microblogging Based on Log-linear Modeling. ASONAM 2012: 189-193 - [c43]Yue Wang, Xintao Wu, Jun Zhu, Yang Xiang:
On Learning Cluster Coefficient of Private Networks. ASONAM 2012: 395-402 - [c42]Zhilin Luo, Yue Wang, Xintao Wu:
Predicting Retweeting Behavior Based on Autoregressive Moving Average Model. WISE 2012: 777-782 - [i1]Yongge Wang, Xintao Wu:
Approximate Inverse Frequent Itemset Mining: Privacy, Complexity, and Approximation. CoRR abs/1207.5466 (2012) - 2011
- [j15]Ling Guo, Xiaowei Ying, Xintao Wu:
Limiting Attribute Disclosure in Randomization Based Microdata Release. J. Comput. Sci. Eng. 5(3): 169-182 (2011) - [j14]Xiaowei Ying, Xintao Wu:
On link privacy in randomizing social networks. Knowl. Inf. Syst. 28(3): 645-663 (2011) - [j13]Xiaowei Ying, Leting Wu, Xintao Wu:
A Spectrum-Based Framework for Quantifying Randomness of Social Networks. IEEE Trans. Knowl. Data Eng. 23(12): 1842-1856 (2011) - [c41]Xiaowei Ying, Xintao Wu, Daniel Barbará:
Spectrum based fraud detection in social networks. ICDE 2011: 912-923 - [c40]Leting Wu, Xiaowei Ying, Xintao Wu, Zhi-Hua Zhou:
Line Orthogonality in Adjacency Eigenspace with Application to Community Partition. IJCAI 2011: 2349-2354 - [c39]Kai Pan, Xintao Wu, Tao Xie:
Generating program inputs for database application testing. ASE 2011: 73-82 - [c38]Leting Wu, Xiaowei Ying, Xintao Wu, Aidong Lu, Zhi-Hua Zhou:
Spectral Analysis of k-Balanced Signed Graphs. PAKDD (2) 2011: 1-12 - [c37]Kai Pan, Xintao Wu, Tao Xie:
Database state generation via dynamic symbolic execution for coverage criteria. DBTest 2011: 4 - 2010
- [c36]Xiaowei Ying, Xintao Wu, Daniel Barbará:
Spectrum based fraud detection in social networks. CCS 2010: 747-749 - [c35]Ling Guo, Xiaowei Ying, Xintao Wu:
On Attribute Disclosure in Randomization Based Privacy Preserving Data Publishing. ICDM Workshops 2010: 466-473 - [c34]Leting Wu, Xiaowei Ying, Xintao Wu:
Reconstruction from Randomized Graph via Low Rank Approximation. SDM 2010: 60-71 - [c33]Lane Harrison, Xianlin Hu, Xiaowei Ying, Aidong Lu, Weichao Wang, Xintao Wu:
Interactive detection of network anomalies via coordinated multiple views. VizSEC 2010: 91-101 - [p2]Xintao Wu, Xiaowei Ying, Kun Liu, Lei Chen:
A Survey of Privacy-Preservation of Graphs and Social Networks. Managing and Mining Graph Data 2010: 421-453
2000 – 2009
- 2009
- [j12]Ling Guo, Xintao Wu:
Privacy Preserving Categorical Data Analysis with Unknown Distortion Parameters. Trans. Data Priv. 2(3): 185-205 (2009) - [c32]Xiaowei Ying, Kai Pan, Xintao Wu, Ling Guo:
Comparisons of randomization and K-degree anonymization schemes for privacy preserving social network publishing. SNAKDD 2009: 10 - [c31]Xiaowei Ying, Xintao Wu:
On Link Privacy in Randomizing Social Networks. PAKDD 2009: 28-39 - [c30]Xiaowei Ying, Xintao Wu:
On Randomness Measures for Social Networks. SDM 2009: 709-720 - [c29]Xiaowei Ying, Xintao Wu:
Graph Generation with Prescribed Feature Constraints. SDM 2009: 966-977 - [p1]Xiaowei Ying, Xintao Wu, Kai Pan, Ling Guo:
On the Quantification of Identity and Link Disclosures in Randomizing Social Networks. Advances in Information and Intelligent Systems 2009: 91-116 - 2008
- [j11]Ling Qiu, Yingjiu Li, Xintao Wu:
Protecting business intelligence and customer privacy while outsourcing data mining tasks. Knowl. Inf. Syst. 17(1): 99-120 (2008) - [j10]Songtao Guo, Xintao Wu, Yingjiu Li:
Determining error bounds for spectral filtering based reconstruction methods in privacy preserving data mining. Knowl. Inf. Syst. 17(2): 217-240 (2008) - [c28]Ling Guo, Songtao Guo, Xintao Wu:
On Addressing Accuracy Concerns in Privacy Preserving Association Rule Mining. PAKDD 2008: 124-135 - [c27]Xiaowei Ying, Xintao Wu:
Randomizing Social Networks: a Spectrum Preserving Approach. SDM 2008: 739-750 - 2007
- [j9]Xintao Wu, Yongge Wang, Songtao Guo, Yuliang Zheng:
Privacy Preserving Database Generation for Database Application Testing. Fundam. Informaticae 78(4): 595-612 (2007) - [j8]Ling Qiu, Yingjiu Li, Xintao Wu:
Preserving privacy in association rule mining with bloom filters. J. Intell. Inf. Syst. 29(3): 253-278 (2007) - [c26]Songtao Guo, Xintao Wu:
Deriving Private Information from Arbitrarily Projected Data. PAKDD 2007: 84-95 - [c25]Ling Guo, Songtao Guo, Xintao Wu:
Privacy Preserving Market Basket Data Analysis. PKDD 2007: 103-114 - 2006
- [j7]Xintao Wu:
Incorporating large unlabeled data to enhance EM classification. J. Intell. Inf. Syst. 26(3): 211-226 (2006) - [j6]Xintao Wu, Yong Ye:
Exploring gene causal interactions using an enhanced constraint-based method. Pattern Recognit. 39(12): 2439-2449 (2006) - [c24]Songtao Guo, Xintao Wu, Yingjiu Li:
Deriving Private Information from Perturbed Data Using IQR Based Approach. ICDE Workshops 2006: 92 - [c23]Ling Qiu, Yingjiu Li, Xintao Wu:
An Approach to Outsourcing Data Mining Tasks while Protecting Business Intelligence and Customer Privacy. ICDM Workshops 2006: 551-558 - [c22]Haibing Lu, Yingjiu Li, Xintao Wu:
Disclosure Risk in Dynamic Two-Dimensional Contingency Tables (Extended Abstract). ICISS 2006: 349-352 - [c21]Songtao Guo, Xintao Wu, Yingjiu Li:
On the Lower Bound of Reconstruction Error for Spectral Filtering Based Privacy Preserving Data Mining. PKDD 2006: 520-527 - [c20]Haibing Lu, Yingjiu Li, Xintao Wu:
Disclosure Analysis for Two-Way Contingency Tables. Privacy in Statistical Databases 2006: 57-67 - [c19]Xintao Wu, Songtao Guo, Yingjiu Li:
Towards value disclosure analysis in modeling general databases. SAC 2006: 617-621 - [c18]Songtao Guo, Xintao Wu:
On the use of spectral filtering for privacy preserving data mining. SAC 2006: 622-626 - 2005
- [c17]Yongge Wang, Xintao Wu:
Approximate Inverse Frequent Itemset Mining: Privacy, Complexity, and Approximation. ICDM 2005: 482-489 - [c16]Xintao Wu, Chintan Sanghvi, Yongge Wang, Yuliang Zheng:
Privacy Aware Data Generation for Testing Database Applications. IDEAS 2005: 317-326 - [c15]Xintao Wu, Yongge Wang, Yuliang Zheng:
Statistical Database Modeling for Privacy Preserving Database Generation. ISMIS 2005: 382-390 - [c14]Yong Ye, Xintao Wu:
Efficient Causal Interaction Learning with Applications in Microarray. ISMIS 2005: 622-630 - [c13]Xintao Wu, Ying Wu, Yongge Wang, Yingjiu Li:
Privacy Aware Market Basket Data Set Generation: A Feasible Approach for Inverse Frequent Set Mining. SDM 2005: 103-114 - 2004
- [c12]Yong Ye, Xintao Wu, Kalpathi R. Subramanian, Liying Zhang:
GenExplore: Interactive Exploration of Gene Interactions from Microarray Data. ICDE 2004: 860 - [c11]Yongge Wang, Xintao Wu, Yuliang Zheng:
Privacy Preserving Data Generation for Database Application Performance Testing. TrustBus 2004: 142-151 - 2003
- [j5]Daniel Barbará, Xintao Wu:
An Approximate Median Polish Algorithm for Large Multidimensional Data Sets. Knowl. Inf. Syst. 5(4): 416-438 (2003) - [j4]Xintao Wu, Yong Ye, Liying Zhang:
Graphical modeling based gene interaction analysis for microarray data. SIGKDD Explor. 5(2): 91-100 (2003) - [c10]Xintao Wu, Daniel Barbará:
Compressing High Dimensional Datasets by Fractals. DCC 2003: 452 - [c9]Xintao Wu, Yong Ye, Kalpathi R. Subramanian:
Interactive Analysis of Gene Interactions Using Graphical gaussian model. BIOKDD 2003: 63-69 - [c8]Xintao Wu, Daniel Barbará, Yong Ye:
Screening and interpreting multi-item associations based on log-linear modeling. KDD 2003: 276-285 - [c7]Xintao Wu, Yongge Wang, Yuliang Zheng:
Privacy preserving database application testing. WPES 2003: 118-128 - 2002
- [j3]Xintao Wu, Daniel Barbará:
Learning missing values from summary constraints. SIGKDD Explor. 4(1): 21-30 (2002) - [c6]Xintao Wu, Daniel Barbará:
Modeling and Imputation of Large Incomplete Multidimensional Datasets. DaWaK 2002: 286-295 - [c5]Xintao Wu, Jianping Fan, Kalpathi R. Subramanian:
B-EM: a classifier incorporating bootstrap with EM approach for data mining. KDD 2002: 670-675 - 2001
- [j2]Daniel Barbará, Xintao Wu:
Loglinear-Based Quasi Cubes. J. Intell. Inf. Syst. 16(3): 255-276 (2001) - [c4]Daniel Barbará, Xintao Wu:
Finding Dense Clusters in Hyperspace: An Approach Based on Row Shuffling. WAIM 2001: 305-316 - 2000
- [c3]Daniel Barbará, Xintao Wu:
Supporting Online Queries in ROLAP. DaWaK 2000: 234-243 - [c2]Daniel Barbará, Xintao Wu:
Using Loglinear Models to Compress Datacube. Web-Age Information Management 2000: 311-322
1990 – 1999
- 1999
- [j1]Daniel Barbará, Xintao Wu:
The Role of Approximations in Maintaining and Using Aggregate Views. IEEE Data Eng. Bull. 22(4): 15-21 (1999) - [c1]Daniel Barbará, Xintao Wu:
Using Approximations to Scale Exploratory Data Analysis in Datacubes. KDD 1999: 382-386
Coauthor Index
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