Publications

Other online scholarship profiles: Google Scholar, DBLP, ACM Author Page, and ORC-ID.

• Differentially private hierarchical count-of-counts histograms
  Yu-Hsuan Kuo, Cho-Chun Chiu, Dan Kifer, Michael Hay, and Ashwin Machanavajjhala
  PVLDB 2018
• Optimizing error of high-dimensional statistical queries under differential privacy
  Ryan McKenna, Gerome Miklau, Michael Hay, and Ashwin Machanavajjhala
  PVLDB 2018
• IoT-Detective: Analyzing IoT Data Under Differential Privacy
  Sameera Ghayyur, Yan Chen, Roberto Yus, Ashwin Machanavajjhala, Michael Hay, Gerome Miklau, and Sharad Mehrotra
  SIGMOD (Demo) 2018
• Ektelo: A Framework for Defining Differentially-Private Computations
  Dan Zhang, Ryan McKenna, Ios Kotsogiannis, Michael Hay, Gerome Miklau, and Ashwin Machanavajjhala
  SIGMOD 2018
• Ektelo: A Framework for Defining Differentially-Private Computations
  Dan Zhang, Ryan McKenna, Ios Kotsogiannis, Michael Hay, Gerome Miklau, and Ashwin Machanavajjhala
  TPDP 2017
• PeGaSus: Data-Adaptive Differentially Private Stream Processing
  Yan Chen, Ashwin Machanavajjhala, Michael Hay, and Gerome Miklau
  CCS 2017
• Differentially Private Learning of Graphical Models Using CGMs
  Garret Bernstein, Ryan McKenna, Tao Sun, Dan Sheldon, Michael Hay, and Gerome Miklau
  ICML 2017
• Differentially Private Learning of Graphical Models Using CGMs
  Garret Bernstein, Ryan McKenna, Tao Sun, Dan Sheldon, Michael Hay, and Gerome Miklau
  Private and Secure Machine Learning Workshop at ICML 2017
• Pythia: Data Dependent Differentially Private Algorithm Selection
  Ios Kotsogiannis, Ashwin Machanavajjhala, Michael Hay, and Gerome Miklau
  SIGMOD 2017
• DIAS: Differentially Private Interactive Algorithm Selection using Pythia
  Ios Kotsogiannis, Michael Hay, Ashwin Machanavajjhala, Gerome Miklau, and Margaret Orr
  SIGMOD (Demo) 2017
• Differential Privacy in the Wild: A tutorial on current practices & open challenges. (Slides)
  Ashwin Machanavajjhala, Xi He, and Michael Hay
  SIGMOD 2017
• Differentially Private Rank Aggregation
  Michael Hay, Gerome Miklau, and Liudmila Elagina
  SDM 2017
• Differential Privacy in the Wild: A tutorial on current practices & open challenges. (Slides)
  Ashwin Machanavajjhala, Xi He, and Michael Hay
  PVLDB 2016
• Exploring Privacy-Accuracy Tradeoffs using DPComp
  Michael Hay, Ashwin Machanavajjhala, Gerome Miklau, Yan Chen, Dan Zhang, and George Bissias
  SIGMOD (Demo) 2016
• Principled Evaluation of Differentially Private Algorithms using DPBench
  Michael Hay, Ashwin Machanavajjhala, Gerome Miklau, Yan Chen, and Dan Zhang
  SIGMOD 2016
• 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 Query Answering Algorithm for Range Queries Under Differential Privacy
  Chao Li, Michael Hay, Gerome Miklau, and Yue Wang
  PVLDB 2014
• Crowd-Blending Privacy
  Johannes Gehrke, Michael Hay, Edward Lui, and Rafael Pass
  Crypto 2012
• iReduct: Differential Privacy with Reduced Relative Errors
  Xiaokui Xiao, Gabriel Bender, Michael Hay, Johannes Gehrke
  SIGMOD 2011
• Privacy-aware Data Management in Information Networks (Tutorial) (Slides)
  Michael Hay, Kun Liu, Gerome Miklau, Jian Pei, and Evimaria Terzi
  SIGMOD 2011
• Enabling Accurate Analysis of Private Network Data
  Michael Hay
  Ph.D. Thesis 2010
• Resisting Structural Re-identification in Anonymized Social Networks
  Michael Hay, Gerome Miklau, David Jensen, Don Towsley, and Chao Li
  VLDB Journal 2010
• Optimizing Linear Counting Queries Under Differential Privacy
  Chao Li, Michael Hay, Vibhor Rastogi, Gerome Miklau, Andrew McGregor
  PODS 2010
• Boosting the Accuracy of Differentially-Private Histograms Through Consistency
  Michael Hay, Vibhor Rastogi, Gerome Miklau, Dan Suciu
  VLDB 2010
• Accurate Estimation of the Degree Distribution of Private Networks
  Michael Hay, Chao Li, Gerome Miklau, David Jensen
  ICDM 2009
• Enabling Accurate Analysis of Private Network Data
  Michael Hay, Gerome Miklau, David Jensen
  Draft book chapter, Privacy-Aware Knowledge Discovery: Novel Applications and New Techniques, Chapman & Hall/CRC Press. 2010
• Relationship Privacy: Output Perturbation for Queries with Joins
  Vibhor Rastogi, Michael Hay, Gerome Miklau, Dan Suciu
  PODS 2009
• Resisting Structural Re-identification in Anonymized Social Networks
  Michael Hay, Gerome Miklau, David Jensen, Don Towsley, and Philipp Weis
  VLDB 2008
• Anonymizing social networks
  Michael Hay, Gerome Miklau, David Jensen, Philipp Weis, and Siddharth Srivastava
  University of Massachusetts Amherst Technical Report 2007
• An integrated, conditional model of information extraction and coreference with application to citation matching
  Ben Wellner, Andrew McCallum, Fuchun Peng and Michael Hay
  UAI 2004
• Exploiting relational structure to understand publication patterns in high-energy physics
  Amy McGovern, Lisa Friedland, Michael Hay, Brian Gallagher, Andrew Fast, Jennifer Neville, David Jensen
  ACM SIGKDD Explorations 2003
• Learning relational probability trees
  Jennifer Neville, David Jensen, Lisa Friedland, and Michael Hay
  SIGKDD 2003
• Avoiding bias when aggregating relational data with degree disparity
  David Jensen, Jennifer Neville, and Michael Hay
  ICML 2003