Publications - By Topic

---

Fairness, Accountability, Transparency

• Fair Decision Making using Privacy-Protected Data
  David Pujol, Satya Kuppam, Ryan Mckenna, Michael Hay, Ashwin Machanavajjhala, Gerome Miklau
  ACM Conference on Fairness, Accountability, and Transparency 2020

• On Obtaining Stable Rankings
  Abolfazl Asudeh, H. V. Jagadish, Gerome Miklau, Julia Stoyanovich
  Proceedings of the VLDB (PVLDB) 2019

• MithraRanking: A System for Responsible Ranking Design
  Yifan Guan, Abolfazl Asudeh, Pranav Mayuram, H. V. Jagadish, Julia Stoyanovich, Gerome Miklau, Gautam Das
  Demo, Conference on Management of Data (SIGMOD) 2019

• Panel: A Debate on Data and Algorithmic Ethics
  Julia Stoyanovich, Bill Howe, J. V. Jagadish, Gerome Miklau
  Proceedings of the VLDB (PVLDB) 2018

• A Nutritional Label for Rankings
  Ke Yang, Julia Stoyanovich, Abolfazl Asudeh, Bill Howe, HV Jagadish, and Gerome Miklau
  Demo, Conference on Management of Data (SIGMOD) 2018

• RC-Index: Diversifying Answers to Range Queries
  Yue Wang, Alexandra Meliou, and Gerome Miklau
  Proceedings of the VLDB (PVLDB) 2018

• Fides: Towards a Platform for Responsible Data Science
  Bill Howe, Julia Stoyanovich, Serge Abiteboul, Gerome Miklau, Arnaud Sahuguet, and Gerhard Weikum
  Conference on Scientific and Statistical Database Management (SSDBM) 2017

• Data, responsibly: Fairness, neutrality and transparency in data analysis
  Julia Stoyanovich, Serge Abiteboul and Gerome Miklau
  Tutorial, Conference on Extending Database Technology (EDBT) 2016

Data Privacy

• COMING SOON AIM: An Adaptive and Iterative Mechanism for Differentially Private Synthetic Data
  Ryan McKenna, Brett Mullins, Daniel Sheldon, Gerome Miklau
  Proceedings of the VLDB (PVLDB) 2022

• Benchmarking Differentially Private Synthetic Data Generation Algorithms
  Yuchao Tao, Ryan McKenna, Michael Hay, Ashwin Machanavajjhala, Gerome Miklau
  Workshop on Privacy-Preserving Artificial Intelligence (PPAI) 2022

• Relaxed Marginal Consistency for Differentially Private Query Answering
  Ryan McKenna, Siddhant Pradhan, Dan Sheldon, Gerome Miklau
  Conference on Neural Information Processing Systems (NeurIPS) 2021

• Winning the NIST Contest: A scalable and general approach to differentially private synthetic data
  Ryan McKenna, Gerome Miklau, Dan Sheldon
  Journal of Privacy and Confidentiality (JPC) 2021

• Differentially Private Algorithms for 2020 Census Detailed DHC Race and Ethnicity
  Sam Haney, William Sexton, Ashwin Machanavajjhala, Michael Hay, Gerome Miklau
  Workshop on Theory and Practice of Differential Privacy (TPDP) 2021

• Investigating Visual Analysis of Differentially Private Data
  Dan Zhang, Ali Sarvghad, Gerome Miklau
  IEEE Conference on Information Visualization (InfoVis) 2020

• A Workload-adaptive Mechanism for Linear Queries Under Local Differential Privacy
  Ryan McKenna, Raj Kumar Maity, Arya Mazumdar, Gerome Miklau
  Proceedings of the VLDB (PVLDB) 2020

• PrivateSQL: A Differentially Private SQL Query Engine
  Ios Kotsogiannis, Yuchao Tao, Xi He, Maryam Fanaeepour, Ashwin Machanavajjhala, Michael Hay, Gerome Miklau
  Proceedings of the VLDB (PVLDB) 2019

• PSynDB: Accurate and Accessible Private Data Generation
  Zhiqi Huang, Ryan McKenna, George Bissias, Gerome Miklau, Michael Hay, Ashwin Machanavajjhala
  Demo, Proceedings of the VLDB (PVLDB) 2019

• Lessons learned from the NIST Differential Privacy Synthetic Data Competition
  Ryan Mckenna and Gerome Miklau
  Workshop on Theory and Practice of Differential Privacy (TPDP) 2019

• Graphical-model based estimation and inference for differential privacy
  Ryan McKenna, Dan Sheldon, Gerome Miklau
  International Conference on Machine Learning (ICML) 2019

• Ektelo: A Framework for Defining Differentially-Private Computations
  Dan Zhang, Ryan McKenna, Ios Kotsogiannis, George Bissias, Michael Hay, Ashwin Machanavajjhala, Gerome Miklau
  SIGMOD Record 2019

• Architecting a Differentially Private SQL Engine
  Ios Kotsogiannis, Yuchao Tao, Ashwin Machanavajjhala, Gerome Miklau, Michael Hay
  Conference on Innovative Data Systems Research (CIDR) 2019

• Optimizing Error of High-Dimensional Statistical Queries Under Differential Privacy
  Ryan McKenna, Gerome Miklau, Michael Hay, Ashwin Machanavajjhala
  Proceedings of the VLDB (PVLDB) 2018

• Ektelo: A Framework for Defining Differentially-Private Computations
  Dan Zhang, Ryan McKenna, Ios Kotsogiannis, Michael Hay, Ashwin Machanavajjhala, Gerome Miklau
  Conference on Management of Data (SIGMOD) 2018

• IoT-Dectective: Analyzing IoT Data Under Differential Privacy
  Sameera Ghayyur, Yan Chen, Roberto Yus, Ashwin Machanavajjhala, Michael Hay, Gerome Miklau, Sharad Mehrotra
  Demo, Conference on Management of Data (SIGMOD) 2018

• PeGaSus: Data-Adaptive Differentially Private Stream Processing
  Yan Chen, Ashwin Machanavajjhala, Michael Hay, Gerome Miklau
  Conference on Computer and Communications Security (CCS) 2017

• Differentially Private Learning of Undirected Graphical Models Using Collective Graphical Models
  Garrett Bernstein, Ryan McKenna, Tao Sun, Daniel Sheldon, Michael Hay and Gerome Miklau
  International Conference on Machine Learning (ICML) 2017

• Differentially Private Rank Aggregation
  Michael Hay, Liudmila Elagina, Gerome Miklau
  SIAM Conference on Data Management (SDM) 2017

• Pythia: Data Dependent Differentially Private Algorithm Selection
  Ios Kotsogiannis, Ashwin Machanavajjhala, Michael Hay, Gerome Miklau
  Conference on Management of Data (SIGMOD) 2017

• DIAS: Differentially Private Interactive Algorithm Selection using Pythia
  Ios Kotsogiannis, Ashwin Machanavajjhala, Michael Hay, Gerome Miklau, Margaret Orr
  Demo, Conference on Management of Data (SIGMOD) 2017

• A Theory of Pricing Private Data
  Chao Li, Daniel Yang Li, Gerome Miklau, and Dan Suciu
  Communications of the ACM, Research Highlight 2017

• Exploring Privacy-Accuracy Tradeoffs using DPComp
  Michael Hay, Ashwin Machanavajjhala, Gerome Miklau, Yan Chen, Dan Zhang and George Bissias
  Demo, Conference on Management of Data (SIGMOD) 2016

• Principled Evaluation of Differentially Private Algorithms using DPBench
  Michael Hay, Ashwin Machanavajjhala, Gerome Miklau, Yan Chen, and Dan Zhang
  Conference on Management of Data (SIGMOD) 2016

• Challenges of Visualizing Differentially Private Data
  Dan Zhang, Michael Hay, Gerome Miklau, and Brendan O'Connor
  Theory and Practice of Differential Privacy Workshop 2016

• Lower bounds on the error of query sets under the differentially-private matrix mechanism
  Chao Li and Gerome Miklau
  Theory of Computing Systems (TOCS) 2015

• The matrix mechanism: optimizing linear counting queries under differential privacy
  Chao Li, Gerome Miklau, Michael Hay, Andrew McGregor and Vibhor Rastogi
  VLDB Journal 2015

• A Data- and Workload-Aware Algorithm for Range Queries Under Differential Privacy
  Chao Li, Michael Hay, Gerome Miklau and Yue Wang
  Proceedings of the VLDB (PVLDB) 2014

• A Data- and Workload-Aware Algorithm for Range Queries Under Differential Privacy
  Chao Li, Michael Hay, Gerome Miklau and Yue Wang
  Full Version of PVLDB 2014, arXiv:1410.0265 2014

• Exponential Random Graph Estimation under Differential Privacy
  Wentian Lu and Gerome Miklau
  Conference on Knowledge Discovery and Data Mining (KDD) 2014

• Generating Private Synthetic Databases for Untrusted System Evaluation
  Wentian Lu, Gerome Miklau, and Vani Gupta
  International Conference on Data Engineering (ICDE) 2014

• A Theory of Pricing Private Data
  Chao Li, Daniel Yang Li, Gerome Miklau, and Dan Suciu
  ACM Transactions on Database Systems (TODS) 2014

• A Theory of Pricing Private Data
  Chao Li, Daniel Yang Li, Gerome Miklau, and Dan Suciu
  International Conference on Database Theory (ICDT) 2013
  Winner, Best Paper Award

• Optimal error of query sets under the differentially-private matrix mechanism
  Chao Li and Gerome Miklau
  International Conference on Database Theory (ICDT) 2013

• Differential privacy in data publication and analysis
  Yin Yang, Zhenjie Zhang, Gerome Miklau, Marianne Winslett, and Xiaokui Xiao
  Conference on Management of Data (SIGMOD), Tutorial Program 2012

• An Adaptive Mechanism for Accurate Query Answering under Differential Privacy
  Chao Li and Gerome Miklau
  Proceedings of the VLDB (PVLDB) 2012

• Measuring the achievable error of query sets under differential privacy
  Chao Li and Gerome Miklau
  CoRR abs/1202.3399 2012

• Pricing Aggregate Queries in a Data Marketplace
  Chao Li and Gerome Miklau
  Workshop on the Web and Databases (WebDB) 2012

• Efficient Batch Query Answering Under Differential Privacy
  Chao Li and Gerome Miklau
  CoRR abs/1103.1367 2011

• Privacy-aware Data Management in Information Networks
  Michael Hay, Kun Liu, Gerome Miklau, Jian Pei, and Evimaria Terzi
  Conference on Management of Data (SIGMOD), Tutorial Program 2011

• Private Database Synthesis for Outsourced System Evaluation
  Vani Gupta, Gerome Miklau, and Neoklis Polyzotis
  Alberto Mendelzon International Workshop on Foundations of Data Management 2011

• Boosting the Accuracy of Differentially-Private Queries Through Consistency
  Michael Hay, Vibhor Rastogi, Gerome Miklau, and Dan Suciu
  Proceedings of the VLDB (PVLDB) 2010

• Optimizing Linear Counting Queries Under Differential Privacy
  Chao Li, Michael Hay, Vibhor Rastogi, Gerome Miklau, and Andrew McGregor
  Principles of Database Systems (PODS) 2010

• Resisting Structural Re-identification in Anonymized Social Networks
  Michael Hay, Gerome Miklau, David Jensen, Don Towsley, Chao Li
  VLDB Journal 2010

• Optimizing Histogram Queries Under Differential Privacy
  Chao Li, Michael Hay, Vibhor Rastogi, Gerome Miklau, and Andrew McGregor
  Full Version of PODS 2010, CoRR abs/0912.4742 2009

• Boosting the Accuracy of Differentially-Private Queries Through Consistency
  Michael Hay, Vibhor Rastogi, Gerome Miklau, and Dan Suciu
  Preprint, CoRR abs/0904.0942 2009

• Accurate Estimation of the Degree Distribution of Private Networks
  Michael Hay, Chao Li, Gerome Miklau, and David Jensen
  International Conference on Data Mining (ICDM) 2009
  Winner, Best Student Paper Award

• A Framework for Safely Publishing Communication Traces
  Abhinav Parate and Gerome Miklau
  Conference on Information and Knowledge Management (CIKM) 2009

• Enabling Accurate Analysis of Private Network Data
  Michael Hay and Gerome Miklau and David Jensen
  Draft book chapter, Privacy-Aware Knowledge Discovery: Novel Applications and New Techniques 2009

• Relationship Privacy: Output Perturbation for Queries with Joins
  Vibhor Rastogi and Michael Hay and Gerome Miklau and Dan Suciu
  Principles of Database Systems (PODS) 2009

• A Framework for Safely Publishing Communication Traces
  Abhinav Parate and Gerome Miklau
  University of Massachusetts, Amherst. Technical Report 2009

• Resisting Structural Identification in Anonymized Social Networks
  Michael Hay, Gerome Miklau, David Jensen, Don Towsley, and Philipp Weis
  Conference on Very Large Databases (VLDB) 2008

• A Framework for Utility-Driven Network Trace Anonymization
  Abhinav Parate and Gerome Miklau
  University of Massachusetts, Amherst. Technical Report 2008

• Anonymizing Social Networks
  Michael Hay, Gerome Miklau, David Jensen, Philipp Weis, and Siddharth Srivastava
  University of Massachusetts, Amherst. Technical Report 2007

• A Formal Analysis of Information Disclosure in Data Exchange
  Gerome Miklau and Dan Suciu
  Journal of Computer and System Sciences (JCSS) 2006

• Asymptotic Conditional Probabilities for Conjunctive Queries
  Nilesh Dalvi and Gerome Miklau and Dan Suciu
  International Conference on Database Theory (ICDT) 2005

• Confidentiality and Integrity in Data Exchange
  Gerome Miklau
  Dissertation, University of Washington 2005
  Winner, 2006 SIGMOD Dissertation Award

• A Formal Analysis of Information Disclosure in Data Exchange
  Gerome Miklau and Dan Suciu
  ACM Conference on Management of Data (SIGMOD) 2004

Database Security

• Collaborative Access Control in WebdamLog
  Vera Zaychik Moffitt, Julia Stoyanovich, Serge Abiteboul and Gerome Miklau
  Conference on Management of Data (SIGMOD) 2015

• Rule-based application development using Webdamlog
  Serge Abiteboul, Emilien Antoine, Gerome Miklau, Julia Stoyanovich, Jules Testard
  Demo, Conference on Management of Data (SIGMOD) 2013

• Introducing Access Control in Webdamlog
  Serge Abiteboul, Emilien Antoine, Gerome Miklau, Julia Stoyanovich, Vera Zaychik Moffitt
  Symposium on Database Programming Languages (DBPL), Invited Paper 2013

• Auditing a Database under Retention Restrictions
  Wentian Lu, Gerome Miklau and Neil Immerman
  VLDB Journal 2013

• Auditing a Database under Retention Restrictions
  Wentian Lu and Gerome Miklau
  International Conference on Data Engineering (ICDE) 2009

• Auditing and Forensic Analysis
  Brian Levine and Gerome Miklau
  Encyclopedia of Database Systems 2009

• AuditGuard: A system for database auditing under retention restrictions
  Wentian Lu and Gerome Miklau
  Demo, Conference on Very Large Databases (VLDB) 2008

• Analyzing Privacy in Enterprise Trace Anonymization
  Bruno Ribiero, Weifeng Chen, Gerome Miklau, Don Towsley
  Network and Distributed System Security Symposium (NDSS) 2008

• Log Sanitization: Auditing a Database Under Retention Restrictions
  Wentian Lu and Gerome Miklau
  University of Massachusetts, Amherst. Technical Report 2008

• Threats to Privacy in the Forensic Analysis of Database Systems
  Patrick Stahlberg and Gerome Miklau and Brian Levine
  Conference on Management of Data (SIGMOD) 2007

• Securing history: Privacy and Accountability in Database Systems
  Gerome Miklau and Brian Levine and Patrick Stahlberg
  Conference on Innovative Data Systems Research (CIDR) 2007

• Implementing a Tamper-Evident Database System
  Gerome Miklau and Dan Suciu
  Asian Computing Science Conference, Data Management on the Web 2005

• Managing Integrity for Data Exchanged on the Web.
  Gerome Miklau and Dan Suciu
  Workshop on the Web and Databases (WebDB) 2005

• Controlling Access to Published Data Using Cryptography
  Gerome Miklau and Dan Suciu
  Conference on Very Large Databases (VLDB) 2003

• Cryptographically Enforced Conditional Access for XML
  Gerome Miklau and Dan Suciu
  Workshop on the Web and Databases (WebDB) 2002

Probabilistic Data

• Scalable Probabilistic Databases with Factor Graphs and MCMC
  Michael Wick, Andrew McCallum, and Gerome Miklau
  Proceedings of the VLDB (PVLDB) 2010

• Learning to Predict the Quality of Contributions to Wikipedia
  Greg Druck, Gerome Miklau, and Andrew McCallum
  AAAI Workshop on Wikipedia and Artificial Intelligence 2008

• Probabilistic Representations for Integrating Unreliable Data Sources
  David Mimno, Andrew McCallum, Gerome Miklau
  Workshop on Information Integration on the Web (IIWeb) 2007

XML/XPath

• Containment and Equivalence for a Fragment of XPath
  Gerome Miklau and Dan Suciu
  Journal of the ACM (JACM) 2004

• Processing XML Streams with Deterministic Automata and Stream Indexes
  Todd J. Green and Ashish Gupta and Gerome Miklau and Makoto Onizuka and Dan Suciu
  ACM Transactions on Database Systems (TODS) 2004

• Processing XML Streams with Deterministic Automata
  Todd J. Green and Gerome Miklau and Makoto Onizuka and Dan Suciu
  International Conference on Database Theory (ICDT) 2003

• Containment and Equivalence for an XPath Fragment
  Gerome Miklau and Dan Suciu
  Symposium on Principles of Database Systems (PODS) 2002

Other

• Lifting the Haze off the Cloud: A Market-Based Approach to Resource Allocation in the Cloud
  Yue Wang, Alexandra Meliou, Gerome Miklau
  Proceedings of the VLDB (PVLDB) 2017

• Efficient Recovery from False State in Distributed Routing Algorithms
  Daniel Gyllstrom, Sudarshan Vasudevan, Jim Kurose, Gerome Miklau
  International IFIP TC 6 Networking Conference (NETWORKING) 2010

• Self-Interested Database Managers Playing The View Maintenance Game
  Hala Mostafa, Victor Lesser, Gerome Miklau
  Conference on Autonomous Agents and Multiagent Systems (AAMAS) 2008