Avoiding Bias when Aggregating Relational Data with Degree Disparity. - David D. Jensen; Jennifer Neville; Michael Hay (ICML, 2003)

Learning relational probability trees. - Jennifer Neville; David D. Jensen; Lisa Friedland; Michael Hay (KDD, 2003)

Exploiting relational structure to understand publication patterns in high-energy physics. - Amy McGovern; Lisa Friedland; Michael Hay; Brian Gallagher; Andrew S. Fast; Jennifer Neville; David D. Jensen (SIGKDD Explor., 2003)

An Integrated, Conditional Model of Information Extraction and Coreference with Appli. - Ben Wellner; Andrew McCallum; Fuchun Peng; Michael Hay (UAI, 2004)

Resisting structural re-identification in anonymized social networks. - Michael Hay; Gerome Miklau; David D. Jensen; Donald F. Towsley; Philipp Weis (Proc. VLDB Endow., 2008)

Accurate Estimation of the Degree Distribution of Private Networks. - Michael Hay; Chao Li 003; Gerome Miklau; David D. Jensen (ICDM, 2009)

Relationship privacy: output perturbation for queries with joins. - Vibhor Rastogi; Michael Hay; Gerome Miklau; Dan Suciu (PODS, 2009)

Boosting the Accuracy of Differentially-Private Queries Through Consistency - Michael Hay; Vibhor Rastogi; Gerome Miklau; Dan Suciu (CoRR, 2009)

Optimizing Histogram Queries under Differential Privacy - Chao Li 003; Michael Hay; Vibhor Rastogi; Gerome Miklau; Andrew McGregor 001 (CoRR, 2009)

Optimizing linear counting queries under differential privacy. - Chao Li 003; Michael Hay; Vibhor Rastogi; Gerome Miklau; Andrew McGregor 001 (PODS, 2010)

Co-located Physical-Layer Network Coding to mitigate passive eavesdropping. - Michael Hay; Basil Saeed; Chung-Horng Lung; Anand Srinivasan (PST, 2010)

Boosting the Accuracy of Differentially Private Histograms Through Consistency. - Michael Hay; Vibhor Rastogi; Gerome Miklau; Dan Suciu (Proc. VLDB Endow., 2010)

Resisting structural re-identification in anonymized social networks. - Michael Hay; Gerome Miklau; David D. Jensen; Donald F. Towsley; Chao Li 003 (VLDB J., 2010)

Privacy-aware data management in information networks. - Michael Hay; Kun Liu 001; Gerome Miklau; Jian Pei 001; Evimaria Terzi (SIGMOD Conference, 2011)

iReduct: differential privacy with reduced relative errors. - Xiaokui Xiao; Gabriel Bender; Michael Hay; Johannes Gehrke (SIGMOD Conference, 2011)

An Integrated, Conditional Model of Information Extraction and Coreference with Applications to Citation Matching - Ben Wellner; Andrew McCallum; Fuchun Peng; Michael Hay (CoRR, 2012)

Crowd-Blending Privacy. - Johannes Gehrke; Michael Hay; Edward Lui; Rafael Pass (IACR Cryptol. ePrint Arch., 2012)

Network Coding and Quality of Service metrics for Mobile Ad-hoc Networks. - Michael Hay; Basil Saeed; Chung-Horng Lung; Thomas Kunz; Anand Srinivasan (IWCMC, 2013)

How PhD students at research universities can prepare for a career at a liberal arts college (abstract only). - Ann Irvine; Darakhshan Mir; Michael Hay (SIGCSE, 2013)

A Data- and Workload-Aware Algorithm for Range Queries Under Differential Privacy. - Chao Li 003; Michael Hay; Gerome Miklau; Yue Wang 070 (CoRR, 2014)

A Data- and Workload-Aware Query Answering Algorithm for Range Queries Under Differential Privacy. - Chao Li 003; Michael Hay; Gerome Miklau; Yue Wang 070 (Proc. VLDB Endow., 2014)

The matrix mechanism: optimizing linear counting queries under differential privacy. - Chao Li 003; Gerome Miklau; Michael Hay; Andrew McGregor 001; Vibhor Rastogi (VLDB J., 2015)

Principled Evaluation of Differentially Private Algorithms using DPBench. - Michael Hay; Ashwin Machanavajjhala; Gerome Miklau; Yan Chen 022; Dan Zhang (SIGMOD Conference, 2016)

Exploring Privacy-Accuracy Tradeoffs using DPComp. - Michael Hay; Ashwin Machanavajjhala; Gerome Miklau; Yan Chen 022; Dan Zhang; George Bissias (SIGMOD Conference, 2016)

Differential Privacy in the Wild: A tutorial on current practices & open challenges. - Ashwin Machanavajjhala; Xi He 001; Michael Hay (Proc. VLDB Endow., 2016)

PeGaSus: Data-Adaptive Differentially Private Stream Processing. - Yan Chen 022; Ashwin Machanavajjhala; Michael Hay; Gerome Miklau (CCS, 2017)

Differentially Private Learning of Undirected Graphical Models Using Collective Graphical Models. - Garrett Bernstein; Ryan McKenna; Tao Sun 008; Daniel Sheldon; Michael Hay; Gerome Miklau (ICML, 2017)

Differentially Private Rank Aggregation. - Michael Hay; Liudmila Elagina; Gerome Miklau (SDM, 2017)

DIAS: Differentially Private Interactive Algorithm Selection using Pythia. - Ios Kotsogiannis; Michael Hay; Ashwin Machanavajjhala; Gerome Miklau; Margaret Orr (SIGMOD Conference, 2017)

Pythia: Data Dependent Differentially Private Algorithm Selection. - Ios Kotsogiannis; Ashwin Machanavajjhala; Michael Hay; Gerome Miklau (SIGMOD Conference, 2017)

IoT-Detective: Analyzing IoT Data Under Differential Privacy. - Sameera Ghayyur; Yan Chen 022; Roberto Yus; Ashwin Machanavajjhala; Michael Hay; Gerome Miklau; Sharad Mehrotra (SIGMOD Conference, 2018)

EKTELO: A Framework for Defining Differentially-Private Computations. - Dan Zhang; Ryan McKenna; Ios Kotsogiannis; Michael Hay; Ashwin Machanavajjhala; Gerome Miklau (SIGMOD Conference, 2018)

Differentially Private Hierarchical Group Size Estimation. - Yu-Hsuan Kuo; Cho-Chun Chiu; Daniel Kifer; Michael Hay; Ashwin Machanavajjhala (CoRR, 2018)

Differentially Private Hierarchical Count-of-Counts Histograms. - Yu-Hsuan Kuo; Cho-Chun Chiu; Daniel Kifer; Michael Hay; Ashwin Machanavajjhala (Proc. VLDB Endow., 2018)

Architecting a Differentially Private SQL Engine. - Ios Kotsogiannis; Yuchao Tao; Ashwin Machanavajjhala; Gerome Miklau; Michael Hay (CIDR, 2019)

PSynDB: Accurate and Accessible Private Data Generation. - Zhiqi Huang; Ryan McKenna; George Bissias; Gerome Miklau; Michael Hay; Ashwin Machanavajjhala (Proc. VLDB Endow., 2019)

PrivateSQL: A Differentially Private SQL Query Engine. - Ios Kotsogiannis; Yuchao Tao; Xi He 001; Maryam Fanaeepour; Ashwin Machanavajjhala; Michael Hay; Gerome Miklau (Proc. VLDB Endow., 2019)

#8712;: A Framework for Defining Differentially-Private Computations. - Dan Zhang; Ryan McKenna; Ios Kotsogiannis; George Bissias; Michael Hay; Ashwin Machanavajjhala; Gerome Miklau (SIGMOD Rec., 2019)

TPDP'20: 6th Workshop on Theory and Practice of Differential Privacy. - Rachel Cummings; Michael Hay (CCS, 2020)

Fair decision making using privacy-protected data. - David Pujol; Ryan McKenna; Satya Kuppam; Michael Hay; Ashwin Machanavajjhala; Gerome Miklau (FAT*, 2020)

ϵKTELO: A Framework for Defining Differentially Private Computations. - Dan Zhang; Ryan McKenna; Ios Kotsogiannis; George Bissias; Michael Hay; Ashwin Machanavajjhala; Gerome Miklau (ACM Trans. Database Syst., 2020)

HDMM: Optimizing error of high-dimensional statistical queries under differential privacy. - Ryan McKenna; Gerome Miklau; Michael Hay; Ashwin Machanavajjhala (CoRR, 2021)

Differentially Private Algorithms for 2020 Census Detailed DHC Race & Ethnicity. - Samuel Haney; William Sexton; Ashwin Machanavajjhala; Michael Hay; Gerome Miklau (CoRR, 2021)

Benchmarking Differentially Private Synthetic Data Generation Algorithms. - Yuchao Tao; Ryan McKenna; Michael Hay; Ashwin Machanavajjhala; Gerome Miklau (CoRR, 2021)

Precision-based attacks and interval refining: how to break, then fix, differential privacy on finite computers. - Samuel Haney; Damien Desfontaines; Luke Hartman; Ruchit Shrestha; Michael Hay (CoRR, 2022)

Tumult Analytics: a robust, easy-to-use, scalable, and expressive framework for differential privacy. - Skye Berghel; Philip Bohannon; Damien Desfontaines; Charles Estes; Samuel Haney; Luke Hartman; Michael Hay; Ashwin Machanavajjhala; Tom Magerlein; Gerome Miklau; Amritha Pai; William Sexton; et al. (CoRR, 2022)

Publishing Wikipedia usage data with strong privacy guarantees. - Temilola Adeleye; Skye Berghel; Damien Desfontaines; Michael Hay; Isaac Johnson 001; Cléo Lemoisson; Ashwin Machanavajjhala; Tom Magerlein; Gabriele Modena; David Pujol; Daniel Simmons-Marengo; Hal Triedman (CoRR, 2023)

Optimizing Error of High-Dimensional Statistical Queries Under Differential Privacy. - Ryan McKenna; Gerome Miklau; Michael Hay; Ashwin Machanavajjhala (J. Priv. Confidentiality, 2023)

Programming Frameworks for Differential Privacy. - Marco Gaboardi; Michael Hay; Salil P. Vadhan (CoRR, 2024)

PHSafe: Disclosure Avoidance for the 2020 Census Supplemental Demographic and Housing Characteristics File (S-DHC). - William Sexton; Skye Berghel; Bayard Carlson; Samuel Haney; Luke Hartman; Michael Hay; Ashwin Machanavajjhala; Gerome Miklau; Amritha Pai; Simran Rajpal; David Pujol; Ruchit Shrestha; et al. (CoRR, 2025)

SafeTab-P: Disclosure Avoidance for the 2020 Census Detailed Demographic and Housing Characteristics File A (Detailed DHC-A). - Samuel Haney; Skye Berghel; Bayard Carlson; Ryan Cumings-Menon; Luke Hartman; Michael Hay; Ashwin Machanavajjhala; Gerome Miklau; Amritha Pai; Simran Rajpal; David Pujol; William Sexton; et al. (CoRR, 2025)

SafeTab-H: Disclosure Avoidance for the 2020 Census Detailed Demographic and Housing Characteristics File B (Detailed DHC-B). - William Sexton; Skye Berghel; Bayard Carlson; Samuel Haney; Luke Hartman; Michael Hay; Ashwin Machanavajjhala; Gerome Miklau; Amritha Pai; Simran Rajpal; David Pujol; Ruchit Shrestha; et al. (CoRR, 2025)