Mark Bun

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Fingerprinting codes and the price of approximate differential privacy

Jonathan Ullman, Salil P. Vadhan, Mark Bun, 2013, STOC.

A Computational Separation between Private Learning and Online Learning pdf

Mark Bun, 2020, NeurIPS.

New Oracle-Efficient Algorithms for Private Synthetic Data Release

Thomas Steinke, Zhiwei Steven Wu, Mark Bun, 2020, ICML.

Efficient, Noise-Tolerant, and Private Learning via Boosting pdf

Mark Bun, Marco Leandro Carmosino, Jessica Sorrell, 2020, COLT 2020.

Concentrated Differential Privacy: Simplifications, Extensions, and Lower Bounds pdf

Thomas Steinke, Mark Bun, T. Steinke, 2016, TCC.

Dual Lower Bounds for Approximate Degree and Markov-Bernstein Inequalities

Justin Thaler, Mark Bun, 2013, ICALP.

Average-Case Averages: Private Algorithms for Smooth Sensitivity and Mean Estimation

Thomas Steinke, Mark Bun, T. Steinke, 2019, NeurIPS.

Quantum algorithms and approximating polynomials for composed functions with shared inputs

Justin Thaler, Robin Kothari, Mark Bun, 2018, Electron. Colloquium Comput. Complex..

New Separations in the Complexity of Differential Privacy

Mark Bun, Mark Bun, 2016 .

Private Hypothesis Selection

Thomas Steinke, Zhiwei Steven Wu, Mark Bun, 2019, IEEE Transactions on Information Theory.

Sign-Rank Can Increase Under Intersection

Nikhil S. Mande, Justin Thaler, Mark Bun, 2019, Electron. Colloquium Comput. Complex..

When is Memorization of Irrelevant Training Data Necessary for High-Accuracy Learning? pdf

Gavin Brown, Kunal Talwar, Vitaly Feldman, 2020, ArXiv.

Dual Polynomials for Collision and Element Distinctness pdf

Justin Thaler, Mark Bun, J. Thaler, 2015, Theory Comput..

Differentially Private Release and Learning of Threshold Functions

Kobbi Nissim, Uri Stemmer, Salil P. Vadhan, 2015, 2015 IEEE 56th Annual Symposium on Foundations of Computer Science.

Controlling Privacy Loss in Survey Sampling (Working Paper) pdf

Marco Gaboardi, Audra McMillan, Mark Bun, 2020, ArXiv.

Approximate Degree and the Complexity of Depth Three Circuits

Justin Thaler, Mark Bun, J. Thaler, 2016, Electron. Colloquium Comput. Complex..

Make Up Your Mind: The Price of Online Queries in Differential Privacy

Thomas Steinke, Jonathan Ullman, Mark Bun, 2016, SODA.

Bridging the Gap between Computer Science and Legal Approaches to Privacy

Thomas Steinke, Urs Gasser, Kobbi Nissim, 2018 .

Fingerprinting Codes and the Price of Approximate Differential Privacy

Jonathan Ullman, Salil P. Vadhan, Mark Bun, 2018, SIAM J. Comput..

A Nearly Optimal Lower Bound on the Approximate Degree of AC^0

Justin Thaler, Mark Bun, J. Thaler, 2017, 2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS).

Differentially Private Submodular Maximization: Data Summarization in Disguise

Andreas Krause, Amin Karbasi, Marko Mitrovic, 2017, ICML.

An Equivalence Between Private Classification and Online Prediction

Roi Livni, Shay Moran, Mark Bun, 2020, 2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS).

A Nearly Optimal Lower Bound on the Approximate Degree of AC0

Justin Thaler, Mark Bun, 2017, Electron. Colloquium Comput. Complex..

The polynomial method strikes back: tight quantum query bounds via dual polynomials

Justin Thaler, Robin Kothari, Mark Bun, 2017, Electron. Colloquium Comput. Complex..

Weighted Polynomial Approximations: Limits for Learning and Pseudorandomness

Thomas Steinke, Mark Bun, T. Steinke, 2014, Electron. Colloquium Comput. Complex..

Dual lower bounds for approximate degree and Markov-Bernstein inequalities pdf

Justin Thaler, Mark Bun, J. Thaler, 2013, Inf. Comput..

Improved Bounds on the Sign-Rank of AC^0

Justin Thaler, Mark Bun, 2016, ICALP.

Differential Privacy: A Primer for a Non-Technical Audience

Thomas Steinke, Micah Altman, Kobbi Nissim, 2018 .

Composable and versatile privacy via truncated CDP

Thomas Steinke, Guy N. Rothblum, Cynthia Dwork, 2018, STOC.

Towards Instance-Optimal Private Query Release pdf

Thomas Steinke, Aleksandar Nikolov, Jaroslaw Blasiok, 2018, SODA.

Order-Revealing Encryption and the Hardness of Private Learning

Mark Zhandry, Mark Bun, Mark Bun, 2015, TCC.

The Large-Error Approximate Degree of AC0

Justin Thaler, Mark Bun, J. Thaler, 2018, Electron. Colloquium Comput. Complex..

Heavy Hitters and the Structure of Local Privacy

Uri Stemmer, Jelani Nelson, Mark Bun, 2017, PODS.

Simultaneous Private Learning of Multiple Concepts

Kobbi Nissim, Uri Stemmer, Mark Bun, 2015, ITCS.

Separating Computational and Statistical Differential Privacy in the Client-Server Model

Salil Vadhan, Yi-Hsiu Chen, Mark Bun, 2016, TCC.

Heavy Hitters and the Structure of Local Privacy

Uri Stemmer, Jelani Nelson, Mark Bun, 2019, ACM Trans. Algorithms.

Hardness Amplification and the Approximate Degree of Constant-Depth Circuits

Justin Thaler, Mark Bun, J. Thaler, 2013, ICALP.

The Large-Error Approximate Degree of AC$^0$

Justin Thaler, Mark Bun, 2021, Theory of Computing.

Differentially Private Correlation Clustering pdf

Janardhan Kulkarni, Mark Bun, Marek Eliás, 2021, ICML.

Sign-rank Can Increase under Intersection

Nikhil S. Mande, Justin Thaler, Mark Bun, 2019, Electron. Colloquium Comput. Complex..

When is memorization of irrelevant training data necessary for high-accuracy learning?

Vitaly Feldman, Kunal Talwar, Mark Bun, 2020, STOC.

Quantum algorithms and approximating polynomials for composed functions with shared inputs

Justin Thaler, Robin Kothari, Mark Bun, 2021, Quantum.

Multiclass versus Binary Differentially Private PAC Learning pdf

Marco Gaboardi, Mark Bun, Satchit Sivakumar, 2021, NeurIPS.

A Teaser for Differential Privacy

Mark Bun, 2017 .

An Equivalence Between Private Classification and Online Prediction

Roi Livni, Shay Moran, Mark Bun, 2020, 2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS).