See also my google scholar profile, but beware of "my" DBLP page.
- Multi-Central Differential Privacy 2020.
- The Discrete Gaussian for Differential Privacy
with Clément Canonne and Gautam Kamath, NeurIPS 2020.
- Reasoning About Generalization via Conditional Mutual Information
with Lydia Zakynthinou, COLT 2020.
- New Oracle-Efficient Algorithms for Private Synthetic Data Release
with Giuseppe Vietri, Grace Tian, Mark Bun, and Steven Wu, ICML 2020.
- Average-Case Averages: Private Algorithms for Smooth Sensitivity and Mean Estimation
with Mark Bun, NeurIPS 2019.
- Private Hypothesis Selection
with Mark Bun, Gautam Kamath, and Zhiwei Steven Wu, NeurIPS 2019.
- Towards Instance-Optimal Private Query Release
with Jaroslaw Blasiok, Mark Bun, and Aleksandar Nikolov, SODA 2019.
- The Limits of Post-Selection Generalization
with Kobbi Nissim, Adam Smith, Uri Stemmer, and Jonathan Ullman, NeurIPS 2018.
- Composable and Versatile Privacy via Truncated CDP
with Mark Bun, Cynthia Dwork, and Guy N. Rothblum, STOC 2018.
- Calibrating Noise to Variance in Adaptive Data Analysis
with Vitaly Feldman, COLT 2018.
- Tight Lower Bounds for Differentially Private Selection
with Jonathan Ullman, FOCS 2017.
- Generalization for Adaptively-chosen Estimators via Stable Median
with Vitaly Feldman, COLT 2017.
- Subgaussian Tail Bounds via Stability Arguments
with Jonathan Ullman, 2017.
- Upper and Lower Bounds for Privacy and Adaptivity in Algorithmic Data Analysis
PhD Thesis, Harvard University 2016.
- Exposed! A Survey of Attacks on Private Data
with Cynthia Dwork, Adam Smith, and Jonathan Ullman, Annual Review of Statistics and Its Application 2017.
- Concentrated Differential Privacy: Simplifications, Extensions, and Lower Bounds
with Mark Bun, TCC 2016-B.
- Make Up Your Mind: The Price of Online Queries in Differential Privacy
with Mark Bun and Jonathan Ullman, SODA 2017.
- Robust Traceability from Trace Amounts
with Cynthia Dwork, Adam Smith, Jonathan Ullman, and Salil Vadhan, FOCS 2015.
- Algorithmic Stability for Adaptive Data Analysis
with Raef Bassily, Kobbi Nissim, Adam Smith, Uri Stemmer, and Jonathan Ullman, STOC 2016.
- Between Pure and Approximate Differential Privacy
with Jonathan Ullman, TPDP 2015 & Journal of Privacy and Confidentiality 2017.
- Weighted Polynomial Approximations: Limits for Learning and Pseudorandomness
with Mark Bun, RANDOM 2015.
- Interactive Fingerprinting Codes and the Hardness of Preventing False Discovery
with Jonathan Ullman, COLT 2015.
- Pseudorandomness and Fourier Growth Bounds for Width 3 Branching Programs
with Salil Vadhan and Andrew Wan, RANDOM 2014 & Theory of Computing 2017.
- Pseudorandomness for Regular Branching Programs via Fourier Analysis
with Omer Reingold and Salil Vadhan, RANDOM 2013.
- Pseudorandomness for Permuatation Branching Programs Without the Group Theory
- Learning Hurdles for Sleeping Experts
with Varun Kanade, ITCS 2012 & Transactions on Computing Theory 2014.
- Hierarchical Heavy Hitters with the Space Saving Algorithm
with Michael Mitzenmacher and Justin Thaler, ALENEX 2012.
- Constructive Notions of Compactness in Apartness Spaces
MSc Thesis, University of Canterbury 2011.
- A Rigorous Extension of the Schonhage-Strassen Integer Multiplication Algorithm Using Complex Interval Arithmetic
with Raazesh Sainudiin, CCA 2010 & Reliable Computing 2013.
Olds and News
- Gautam Kamath, Seša Slavković, Adam Smith, Jon Ullman, and I are organizing a Workshop on Differential Privacy and Statistical Data Analysis at The Fields Institute in Toronto 13-17 June 2022.
- I recently moved to Google.
- Check out DifferentialPrivacy.org.
- I mentored Vikrant Singhal and Lydia Zakynthinou as 2020 IBM summer interns.
- Clément Canonne has joined the IBM Almaden theory group as a Goldstine postdoctoral fellow.
- I mentored Lydia Zakynthinou as a 2019 IBM summer intern.
- Marco Gaboardi, Jun Sakuma, and I are organizing a workshop on Differential Privacy and its Applications in Japan
in mid 2020 8-12 November 2021.
- See here for some open problems in differential privacy, including two from me.
- For Spring 2019, I was visiting the Simons Institute for the Theory of Computing at UC Berkeley for the Data Privacy: Foundations and Applications program.
- Mark Bun, Cynthia Dwork, Toniann Pitassi, Guy Rothblum, Kunal Talwar, and I organized a workshop on the Mathematical Foundations of Data Privacy in April/May 2018 in Banff, Canada.
- Steinke is a german name meaning little stone. (Stein means stone or rock and -ke is a diminutive suffix.) The "correct" pronounciation is, approximately, Shteyn-keh, but I sometimes am lazy and use the anglicized pronounciation of Styne-key. I honestly don't care how it is pronounced, as long as it is vaguely recognizable and does not smell bad. My preferred name is Thomas and my preferred pronouns are he/him/his, but they/them/their is also acceptable.
Last updated September 2020 by Thomas Steinke.