Xintao Wu

Orcid: 0000-0002-2823-3063

According to our database1, Xintao Wu authored at least 212 papers between 1999 and 2024.

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Bibliography

2024
WSA-YOLOv5s: improved YOLOv5s based on window self-attention module for ship detection.
Pattern Anal. Appl., December, 2024

Dynamic Environment Responsive Online Meta-Learning with Fairness Awareness.
ACM Trans. Knowl. Discov. Data, July, 2024

From Identifiable Causal Representations to Controllable Counterfactual Generation: A Survey on Causal Generative Modeling.
Trans. Mach. Learn. Res., 2024

Soft Prompting for Unlearning in Large Language Models.
CoRR, 2024

Beyond Human Vision: The Role of Large Vision Language Models in Microscope Image Analysis.
CoRR, 2024

Privacy Preserving Prompt Engineering: A Survey.
CoRR, 2024

DP-TabICL: In-Context Learning with Differentially Private Tabular Data.
CoRR, 2024

In-Context Learning Demonstration Selection via Influence Analysis.
CoRR, 2024

Local Differential Privacy in Graph Neural Networks: a Reconstruction Approach.
Proceedings of the 2024 SIAM International Conference on Data Mining, 2024

Achieving Counterfactual Explanation for Sequence Anomaly Detection.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track and Demo Track, 2024

Robust Influence-Based Training Methods for Noisy Brain MRI.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2024

3rd Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI).
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Algorithmic Fairness Generalization under Covariate and Dependence Shifts Simultaneously.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

On Prediction Feature Assignment in the Heckman Selection Model.
Proceedings of the International Joint Conference on Neural Networks, 2024

Evaluating the Impact of Local Differential Privacy on Utility Loss via Influence Functions.
Proceedings of the International Joint Conference on Neural Networks, 2024

Cascading Failure Prediction in Power Grid Using Node and Edge Attributed Graph Neural Networks.
Proceedings of the International Joint Conference on Neural Networks, 2024

Supervised Algorithmic Fairness in Distribution Shifts: A Survey.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Learning Causally Disentangled Representations via the Principle of Independent Causal Mechanisms.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Contrastive Learning for Fraud Detection from Noisy Labels.
Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

Causal Diffusion Autoencoders: Toward Counterfactual Generation via Diffusion Probabilistic Models.
Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

On Large Visual Language Models for Medical Imaging Analysis: An Empirical Study.
Proceedings of the IEEE/ACM Conference on Connected Health: Applications, 2024

Robustly Improving Bandit Algorithms with Confounded and Selection Biased Offline Data: A Causal Approach.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
The statistical fairness field guide: perspectives from social and formal sciences.
AI Ethics, February, 2023

Fairness-Aware Domain Generalization under Covariate and Dependence Shifts.
CoRR, 2023

Detecting and Correcting Hate Speech in Multimodal Memes with Large Visual Language Model.
CoRR, 2023

Robust Fraud Detection via Supervised Contrastive Learning.
CoRR, 2023

Investigating the Impact of Skill-Related Videos on Online Learning.
Proceedings of the Tenth ACM Conference on Learning @ Scale, 2023

Towards Fair Disentangled Online Learning for Changing Environments.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

2nd Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI).
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

HINT: Healthy Influential-Noise based Training to Defend against Data Poisoning Attacks.
Proceedings of the IEEE International Conference on Data Mining, 2023

Robust Fraud Detection via Supervised Contrastive Learning.
Proceedings of the IEEE International Conference on Big Data, 2023

A Robust Classifier under Missing-Not-at-Random Sample Selection Bias.
Proceedings of the IEEE International Conference on Big Data, 2023

Mitigating Confounding and Selection Biases in Personalized Recommendation: A Causal Approach.
Proceedings of the IEEE International Conference on Big Data, 2023

Randomized Response Has No Disparate Impact on Model Accuracy.
Proceedings of the IEEE International Conference on Big Data, 2023

2022
Achieving User-Side Fairness in Contextual Bandits.
Hum. Centric Intell. Syst., September, 2022

Modeling and reliability verification of industrial control network protocol based on time state transition matrix.
Int. J. Commun. Syst., 2022

The Causal Fairness Field Guide: Perspectives From Social and Formal Sciences.
Frontiers Big Data, 2022

Using Dirichlet Marked Hawkes Processes for Insider Threat Detection.
DTRAP, 2022

Fine-grained Anomaly Detection in Sequential Data via Counterfactual Explanations.
CoRR, 2022

Trustworthy Anomaly Detection: A Survey.
CoRR, 2022

Model Transferring Attacks to Backdoor HyperNetwork in Personalized Federated Learning.
CoRR, 2022

The Fairness Field Guide: Perspectives from Social and Formal Sciences.
CoRR, 2022

Coded Hate Speech Detection via Contextual Information.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2022

Adaptive Fairness-Aware Online Meta-Learning for Changing Environments.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

1st ACM SIGKDD Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI-KDD22).
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Few-shot Anomaly Detection and Classification Through Reinforced Data Selection.
Proceedings of the IEEE International Conference on Data Mining, 2022

Contrastive Learning for Insider Threat Detection.
Proceedings of the Database Systems for Advanced Applications, 2022

Poisoning Attacks on Fair Machine Learning.
Proceedings of the Database Systems for Advanced Applications, 2022

Defending Evasion Attacks via Adversarially Adaptive Training.
Proceedings of the IEEE International Conference on Big Data, 2022

Heterogeneous Randomized Response for Differential Privacy in Graph Neural Networks.
Proceedings of the IEEE International Conference on Big Data, 2022

Fraud Detection via Contrastive Positive Unlabeled Learning.
Proceedings of the IEEE International Conference on Big Data, 2022

SCM-VAE: Learning Identifiable Causal Representations via Structural Knowledge.
Proceedings of the IEEE International Conference on Big Data, 2022

InfoFair: Information-Theoretic Intersectional Fairness.
Proceedings of the IEEE International Conference on Big Data, 2022

Fair Regression under Sample Selection Bias.
Proceedings of the IEEE International Conference on Big Data, 2022

Robust Personalized Federated Learning under Demographic Fairness Heterogeneity.
Proceedings of the IEEE International Conference on Big Data, 2022

Fair Collective Classification in Networked Data.
Proceedings of the IEEE International Conference on Big Data, 2022

Achieving Counterfactual Fairness for Causal Bandit.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
oGBAC - A Group Based Access Control Framework for Information Sharing in Online Social Networks.
IEEE Trans. Dependable Secur. Comput., 2021

Towards Learning-Based, Content-Agnostic Detection of Social Bot Traffic.
IEEE Trans. Dependable Secur. Comput., 2021

Enhancing personalized modeling via weighted and adversarial learning.
Int. J. Data Sci. Anal., 2021

MathBERT: A Pre-trained Language Model for General NLP Tasks in Mathematics Education.
CoRR, 2021

Robust Fairness-aware Learning Under Sample Selection Bias.
CoRR, 2021

Classifying Math KCs via Task-Adaptive Pre-Trained BERT.
CoRR, 2021

MultiFair: Multi-Group Fairness in Machine Learning.
CoRR, 2021

Deep learning for insider threat detection: Review, challenges and opportunities.
Comput. Secur., 2021

Attent: Active Attributed Network Alignment.
Proceedings of the WWW '21: The Web Conference 2021, 2021

Fairness-aware Agnostic Federated Learning.
Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

Transferable Contextual Bandits with Prior Observations.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2021

Managing Uncertainty in Crowdsourcing with Interval-Valued Labels.
Proceedings of the Explainable AI and Other Applications of Fuzzy Techniques, 2021

Removing Disparate Impact on Model Accuracy in Differentially Private Stochastic Gradient Descent.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

LogBERT: Log Anomaly Detection via BERT.
Proceedings of the International Joint Conference on Neural Networks, 2021

A Modeling and Verification Method of Modbus TCP/IP Protocol.
Proceedings of the Algorithms and Architectures for Parallel Processing, 2021

Fair and Robust Classification Under Sample Selection Bias.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Hidden Buyer Identification in Darknet Markets via Dirichlet Hawkes Process.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

Achieving Differential Privacy in Vertically Partitioned Multiparty Learning.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

Fairness-aware Bandit-based Recommendation.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

Classifying Math Knowledge Components via Task-Adaptive Pre-Trained BERT.
Proceedings of the Artificial Intelligence in Education - 22nd International Conference, 2021

A Generative Adversarial Framework for Bounding Confounded Causal Effects.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Removing Disparate Impact of Differentially Private Stochastic Gradient Descent on Model Accuracy.
CoRR, 2020

Fairness through Equality of Effort.
Proceedings of the Companion of The 2020 Web Conference 2020, 2020

Multi-cause Discrimination Analysis Using Potential Outcomes.
Proceedings of the Social, Cultural, and Behavioral Modeling, 2020

Fair Multiple Decision Making Through Soft Interventions.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Database-Access Performance Antipatterns in Database-Backed Web Applications.
Proceedings of the IEEE International Conference on Software Maintenance and Evolution, 2020

AdvPL: Adversarial Personalized Learning.
Proceedings of the 7th IEEE International Conference on Data Science and Advanced Analytics, 2020

Few-shot Insider Threat Detection.
Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

2019
Causal Modeling-Based Discrimination Discovery and Removal: Criteria, Bounds, and Algorithms.
IEEE Trans. Knowl. Data Eng., 2019

Bayesian Network Construction and Genotype-Phenotype Inference Using GWAS Statistics.
IEEE ACM Trans. Comput. Biol. Bioinform., 2019

Identifying Hidden Buyers in Darknet Markets via Dirichlet Hawkes Process.
CoRR, 2019

Achieving Differential Privacy and Fairness in Logistic Regression.
Proceedings of the Companion of The 2019 World Wide Web Conference, 2019

On Convexity and Bounds of Fairness-aware Classification.
Proceedings of the World Wide Web Conference, 2019

Characteristics of Bitcoin Transactions on Cryptomarkets.
Proceedings of the Security, Privacy, and Anonymity in Computation, Communication, and Storage, 2019

Dynamic Anomaly Detection Using Vector Autoregressive Model.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2019

PC-Fairness: A Unified Framework for Measuring Causality-based Fairness.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Achieving Causal Fairness through Generative Adversarial Networks.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Counterfactual Fairness: Unidentification, Bound and Algorithm.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Heterogeneous Gaussian Mechanism: Preserving Differential Privacy in Deep Learning with Provable Robustness.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

BotFlowMon: Learning-based, Content-Agnostic Identification of Social Bot Traffic Flows.
Proceedings of the 7th IEEE Conference on Communications and Network Security, 2019

Insider Threat Detection via Hierarchical Neural Temporal Point Processes.
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

FairGAN<sup>+</sup>: Achieving Fair Data Generation and Classification through Generative Adversarial Nets.
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

SAFE: A Neural Survival Analysis Model for Fraud Early Detection.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

One-Class Adversarial Nets for Fraud Detection.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Incorporating pre-training in long short-term memory networks for tweet classification.
Soc. Netw. Anal. Min., 2018

On spectral analysis of directed signed graphs.
Int. J. Data Sci. Anal., 2018

Task-specific word identification from short texts using a convolutional neural network.
Intell. Data Anal., 2018

Fairness-aware Classification: Criterion, Convexity, and Bounds.
CoRR, 2018

DPNE: Differentially Private Network Embedding.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2018

On Discrimination Discovery and Removal in Ranked Data using Causal Graph.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Achieving Non-Discrimination in Prediction.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

FairGAN: Fairness-aware Generative Adversarial Networks.
Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

2017
On Spectral Analysis of Signed and Dispute Graphs: Application to Community Structure.
IEEE Trans. Knowl. Data Eng., 2017

Preserving differential privacy in convolutional deep belief networks.
Mach. Learn., 2017

Anti-discrimination learning: a causal modeling-based framework.
Int. J. Data Sci. Anal., 2017

Wikipedia Vandal Early Detection: From User Behavior to User Embedding.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

SNE: Signed Network Embedding.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2017

Differential Privacy Preserving Causal Graph Discovery.
Proceedings of the IEEE Symposium on Privacy-Aware Computing, 2017

DPWeka: Achieving Differential Privacy in WEKA.
Proceedings of the IEEE Symposium on Privacy-Aware Computing, 2017

Achieving Non-Discrimination in Data Release.
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

A Causal Framework for Discovering and Removing Direct and Indirect Discrimination.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Adaptive Laplace Mechanism: Differential Privacy Preservation in Deep Learning.
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

On Spectral Analysis of Directed Signed Graphs.
Proceedings of the 2017 IEEE International Conference on Data Science and Advanced Analytics, 2017

Spectrum-based Deep Neural Networks for Fraud Detection.
Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017

Modeling SNP and quantitative trait association from GWAS catalog using CLG Bayesian network.
Proceedings of the 2017 IEEE International Conference on Bioinformatics and Biomedicine, 2017

STIP: An SNP-trait inference platform.
Proceedings of the 2017 IEEE International Conference on Bioinformatics and Biomedicine, 2017

2016
On digital image trustworthiness.
Appl. Soft Comput., 2016

On Discrimination Discovery Using Causal Networks.
Proceedings of the Social, Cultural, and Behavioral Modeling, 9th International Conference, 2016

Situation Testing-Based Discrimination Discovery: A Causal Inference Approach.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Incorporating Pre-Training in Long Short-Term Memory Networks for Tweets Classification.
Proceedings of the IEEE 16th International Conference on Data Mining, 2016

A Two Phase Deep Learning Model for Identifying Discrimination from Tweets.
Proceedings of the 19th International Conference on Extending Database Technology, 2016

Using Randomized Response for Differential Privacy Preserving Data Collection.
Proceedings of the Workshops of the EDBT/ICDT 2016 Joint Conference, 2016

A Framework of Privacy Decision Recommendation for Image Sharing in Online Social Networks.
Proceedings of the IEEE First International Conference on Data Science in Cyberspace, 2016

Using Loglinear Model for Discrimination Discovery and Prevention.
Proceedings of the 2016 IEEE International Conference on Data Science and Advanced Analytics, 2016

Infringement of Individual Privacy via Mining Differentially Private GWAS Statistics.
Proceedings of the Big Data Computing and Communications - Second International Conference, 2016

Building Bayesian networks from GWAS statistics based on Independence of Causal Influence.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2016

Social network dominance based on analysis of asymmetry.
Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2016

Differential Privacy Preservation for Deep Auto-Encoders: an Application of Human Behavior Prediction.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Pairwised Specific Distance Learning from Physical Linkages.
ACM Trans. Knowl. Discov. Data, 2015

Guest Editorial for Special Section on BIBM 2013.
IEEE ACM Trans. Comput. Biol. Bioinform., 2015

Security and privacy protocols for perceptual image hashing.
Int. J. Sens. Networks, 2015

Program-input generation for testing database applications using existing database states.
Autom. Softw. Eng., 2015

On Burst Detection and Prediction in Retweeting Sequence.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2015

Regression Model Fitting under Differential Privacy and Model Inversion Attack.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Analysis of Spectral Space Properties of Directed Graphs Using Matrix Perturbation Theory with Application in Graph Partition.
Proceedings of the 2015 IEEE International Conference on Data Mining, 2015

Block-Organized Topology Visualization for Visual Exploration of Signed Networks.
Proceedings of the IEEE International Conference on Data Mining Workshop, 2015

2014
Guided test generation for database applications via synthesized database interactions.
ACM Trans. Softw. Eng. Methodol., 2014

On Spectral Analysis of Signed and Dispute Graphs.
Proceedings of the 2014 IEEE International Conference on Data Mining, 2014

2013
Preserving Differential Privacy in Degree-Correlation based Graph Generation.
Trans. Data Priv., 2013

On learning cluster coefficient of private networks.
Soc. Netw. Anal. Min., 2013

A spectral approach to detecting subtle anomalies in graphs.
J. Intell. Inf. Syst., 2013

Spectrum-Based Network Visualization for Topology Analysis.
IEEE Computer Graphics and Applications, 2013

On Linear Refinement of Differential Privacy-Preserving Query Answering.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2013

Differential Privacy Preserving Spectral Graph Analysis.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2013

Automatic test generation for mutation testing on database applications.
Proceedings of the 8th International Workshop on Automation of Software Test, 2013

Using aggregate human genome data for individual identification.
Proceedings of the 2013 IEEE International Conference on Bioinformatics and Biomedicine, 2013

2012
Examining spectral space of complex networks with positive and negative links.
Int. J. Soc. Netw. Min., 2012

Predicting Retweeting Behavior Based on Autoregressive Moving Average Model.
Proceedings of the Web Information Systems Engineering - WISE 2012, 2012

Examining Multi-factor Interactions in Microblogging Based on Log-linear Modeling.
Proceedings of the International Conference on Advances in Social Networks Analysis and Mining, 2012

2011
A Spectrum-Based Framework for Quantifying Randomness of Social Networks.
IEEE Trans. Knowl. Data Eng., 2011

On link privacy in randomizing social networks.
Knowl. Inf. Syst., 2011

Limiting Attribute Disclosure in Randomization Based Microdata Release.
J. Comput. Sci. Eng., 2011

Database state generation via dynamic symbolic execution for coverage criteria.
Proceedings of the Fourth International Workshop on Testing Database Systems, 2011

Spectral Analysis of <i>k</i>-Balanced Signed Graphs.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2011

Generating program inputs for database application testing.
Proceedings of the 26th IEEE/ACM International Conference on Automated Software Engineering (ASE 2011), 2011

Line Orthogonality in Adjacency Eigenspace with Application to Community Partition.
Proceedings of the IJCAI 2011, 2011

2010
A Survey of Privacy-Preservation of Graphs and Social Networks.
Proceedings of the Managing and Mining Graph Data, 2010

Interactive detection of network anomalies via coordinated multiple views.
Proceedings of the 7th International Symposium on Visualization for Cyber Security, 2010

Reconstruction from Randomized Graph via Low Rank Approximation.
Proceedings of the SIAM International Conference on Data Mining, 2010

On Attribute Disclosure in Randomization Based Privacy Preserving Data Publishing.
Proceedings of the ICDMW 2010, 2010

Spectrum based fraud detection in social networks.
Proceedings of the 17th ACM Conference on Computer and Communications Security, 2010

2009
On the Quantification of Identity and Link Disclosures in Randomizing Social Networks.
Proceedings of the Advances in Information and Intelligent Systems, 2009

Privacy Preserving Categorical Data Analysis with Unknown Distortion Parameters.
Trans. Data Priv., 2009

Graph Generation with Prescribed Feature Constraints.
Proceedings of the SIAM International Conference on Data Mining, 2009

On Randomness Measures for Social Networks.
Proceedings of the SIAM International Conference on Data Mining, 2009

Comparisons of randomization and K-degree anonymization schemes for privacy preserving social network publishing.
Proceedings of the 3rd Workshop on Social Network Mining and Analysis, 2009

2008
Protecting business intelligence and customer privacy while outsourcing data mining tasks.
Knowl. Inf. Syst., 2008

Determining error bounds for spectral filtering based reconstruction methods in privacy preserving data mining.
Knowl. Inf. Syst., 2008

Randomizing Social Networks: a Spectrum Preserving Approach.
Proceedings of the SIAM International Conference on Data Mining, 2008

On Addressing Accuracy Concerns in Privacy Preserving Association Rule Mining.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2008

2007
Preserving privacy in association rule mining with bloom filters.
J. Intell. Inf. Syst., 2007

Privacy Preserving Database Generation for Database Application Testing.
Fundam. Informaticae, 2007

Privacy Preserving Market Basket Data Analysis.
Proceedings of the Knowledge Discovery in Databases: PKDD 2007, 2007

Deriving Private Information from Arbitrarily Projected Data.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2007

2006
Exploring gene causal interactions using an enhanced constraint-based method.
Pattern Recognit., 2006

Incorporating large unlabeled data to enhance EM classification.
J. Intell. Inf. Syst., 2006

Towards value disclosure analysis in modeling general databases.
Proceedings of the 2006 ACM Symposium on Applied Computing (SAC), 2006

On the use of spectral filtering for privacy preserving data mining.
Proceedings of the 2006 ACM Symposium on Applied Computing (SAC), 2006

Disclosure Analysis for Two-Way Contingency Tables.
Proceedings of the Privacy in Statistical Databases, 2006

On the Lower Bound of Reconstruction Error for Spectral Filtering Based Privacy Preserving Data Mining.
Proceedings of the Knowledge Discovery in Databases: PKDD 2006, 2006

Disclosure Risk in Dynamic Two-Dimensional Contingency Tables (Extended Abstract).
Proceedings of the Information Systems Security, Second International Conference, 2006

An Approach to Outsourcing Data Mining Tasks while Protecting Business Intelligence and Customer Privacy.
Proceedings of the Workshops Proceedings of the 6th IEEE International Conference on Data Mining (ICDM 2006), 2006

Deriving Private Information from Perturbed Data Using IQR Based Approach.
Proceedings of the 22nd International Conference on Data Engineering Workshops, 2006

2005
Privacy Aware Market Basket Data Set Generation: A Feasible Approach for Inverse Frequent Set Mining.
Proceedings of the 2005 SIAM International Conference on Data Mining, 2005

Efficient Causal Interaction Learning with Applications in Microarray.
Proceedings of the Foundations of Intelligent Systems, 15th International Symposium, 2005

Statistical Database Modeling for Privacy Preserving Database Generation.
Proceedings of the Foundations of Intelligent Systems, 15th International Symposium, 2005

Privacy Aware Data Generation for Testing Database Applications.
Proceedings of the Ninth International Database Engineering and Applications Symposium (IDEAS 2005), 2005

Approximate Inverse Frequent Itemset Mining: Privacy, Complexity, and Approximation.
Proceedings of the 5th IEEE International Conference on Data Mining (ICDM 2005), 2005

2004
Privacy Preserving Data Generation for Database Application Performance Testing.
Proceedings of the Trust and Privacy in Digital Business, First International Conference, 2004

GenExplore: Interactive Exploration of Gene Interactions from Microarray Data.
Proceedings of the 20th International Conference on Data Engineering, 2004

2003
Graphical modeling based gene interaction analysis for microarray data.
SIGKDD Explor., 2003

An Approximate Median Polish Algorithm for Large Multidimensional Data Sets.
Knowl. Inf. Syst., 2003

Privacy preserving database application testing.
Proceedings of the 2003 ACM Workshop on Privacy in the Electronic Society, 2003

Interactive Analysis of Gene Interactions Using Graphical gaussian model.
Proceedings of the 3nd ACM SIGKDD Workshop on Data Mining in Bioinformatics (BIOKDD 2003), 2003

Screening and interpreting multi-item associations based on log-linear modeling.
Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 24, 2003

Compressing High Dimensional Datasets by Fractals.
Proceedings of the 2003 Data Compression Conference (DCC 2003), 2003

2002
Learning missing values from summary constraints.
SIGKDD Explor., 2002

B-EM: a classifier incorporating bootstrap with EM approach for data mining.
Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2002

Modeling and Imputation of Large Incomplete Multidimensional Datasets.
Proceedings of the Data Warehousing and Knowledge Discovery, 4th International Conference, 2002

2001
Loglinear-Based Quasi Cubes.
J. Intell. Inf. Syst., 2001

Finding Dense Clusters in Hyperspace: An Approach Based on Row Shuffling.
Proceedings of the Advances in Web-Age Information Management, 2001

2000
Using Loglinear Models to Compress Datacube.
Proceedings of the Web-Age Information Management, First International Conference, 2000

Supporting Online Queries in ROLAP.
Proceedings of the Data Warehousing and Knowledge Discovery, 2000

1999
The Role of Approximations in Maintaining and Using Aggregate Views.
IEEE Data Eng. Bull., 1999

Using Approximations to Scale Exploratory Data Analysis in Datacubes.
Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 1999


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