Badih Ghazi

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Private Counting of Distinct and k-Occurring Items in Time Windows.

[BibT_eX]

[DOI]

Proceedings of the 14th Innovations in Theoretical Computer Science Conference, 2023

Algorithms with More Granular Differential Privacy Guarantees.

[BibT_eX]

[DOI]

Proceedings of the 14th Innovations in Theoretical Computer Science Conference, 2023

On User-Level Private Convex Optimization.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Regression with Label Differential Privacy.

[BibT_eX]

[DOI]

Avinash V. Varadarajan

Chiyuan Zhang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

On Differentially Private Counting on Trees.

[BibT_eX]

[DOI]

Proceedings of the 50th International Colloquium on Automata, Languages, and Programming, 2023

Towards Separating Computational and Statistical Differential Privacy.

[BibT_eX]

[DOI]

Proceedings of the 64th IEEE Annual Symposium on Foundations of Computer Science, 2023

Ticketed Learning-Unlearning Schemes.

[BibT_eX]

[DOI]

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

Differentially Private Aggregation via Imperfect Shuffling.

[BibT_eX]

[DOI]

Proceedings of the 4th Conference on Information-Theoretic Cryptography, 2023

Private Ad Modeling with DP-SGD.

[BibT_eX]

[DOI]

Avinash V. Varadarajan

Chiyuan Zhang

Proceedings of the Workshop on Data Mining for Online Advertising (AdKDD 2023) co-located with the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023), 2023

Optimizing Hierarchical Queries for the Attribution Reporting API.

[BibT_eX]

[DOI]

Proceedings of the Workshop on Data Mining for Online Advertising (AdKDD 2023) co-located with the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023), 2023

Differentially Private Heatmaps.

[BibT_eX]

[DOI]

Nachiappan Valliappan

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Private Aggregation of Trajectories.

[BibT_eX]

[DOI]

Proc. Priv. Enhancing Technol., 2022

Multiparty Reach and Frequency Histogram: Private, Secure, and Practical.

[BibT_eX]

[DOI]

Proc. Priv. Enhancing Technol., 2022

Connect the Dots: Tighter Discrete Approximations of Privacy Loss Distributions.

[BibT_eX]

[DOI]

Proc. Priv. Enhancing Technol., 2022

Distributed, Private, Sparse Histograms in the Two-Server Model.

[BibT_eX]

[DOI]

IACR Cryptol. ePrint Arch., 2022

Differentially Private All-Pairs Shortest Path Distances: Improved Algorithms and Lower Bounds.

[BibT_eX]

[DOI]

CoRR, 2022

Private Isotonic Regression.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Anonymized Histograms in Intermediate Privacy Models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Faster Privacy Accounting via Evolving Discretization.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Large-Scale Differentially Private BERT.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Private Rank Aggregation in Central and Local Models.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Advances and Open Problems in Federated Learning.

[BibT_eX]

[DOI]

Rafael G. L. D'Oliveira

Ananda Theertha Suresh

Found. Trends Mach. Learn., 2021

User-Level Private Learning via Correlated Sampling.

[BibT_eX]

[DOI]

CoRR, 2021

Google COVID-19 Vaccination Search Insights: Anonymization Process Description.

[BibT_eX]

[DOI]

CoRR, 2021

Sample-efficient proper PAC learning with approximate differential privacy.

[BibT_eX]

[DOI]

Proceedings of the STOC '21: 53rd Annual ACM SIGACT Symposium on Theory of Computing, 2021

User-Level Differentially Private Learning via Correlated Sampling.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Deep Learning with Label Differential Privacy.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On Distributed Differential Privacy and Counting Distinct Elements.

[BibT_eX]

[DOI]

Proceedings of the 12th Innovations in Theoretical Computer Science Conference, 2021

Differentially Private Aggregation in the Shuffle Model: Almost Central Accuracy in Almost a Single Message.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Locally Private k-Means in One Round.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

On the Power of Multiple Anonymous Messages: Frequency Estimation and Selection in the Shuffle Model of Differential Privacy.

[BibT_eX]

[DOI]

Proceedings of the Advances in Cryptology - EUROCRYPT 2021, 2021

On Avoiding the Union Bound When Answering Multiple Differentially Private Queries.

[BibT_eX]

[DOI]

Proceedings of the Conference on Learning Theory, 2021

Near-tight closure b ounds for the Littlestone and threshold dimensions.

[BibT_eX]

[DOI]

Proceedings of the Algorithmic Learning Theory, 2021

Robust and Private Learning of Halfspaces.

[BibT_eX]

[DOI]

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Optimality of Correlated Sampling Strategies.

[BibT_eX]

[DOI]

Theory Comput., 2020

Near-tight closure bounds for Littlestone and threshold dimensions.

[BibT_eX]

[DOI]

CoRR, 2020

Differentially Private Clustering: Tight Approximation Ratios.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Private Counting from Anonymous Messages: Near-Optimal Accuracy with Vanishing Communication Overhead.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Pure Differentially Private Summation from Anonymous Messages.

[BibT_eX]

[DOI]

Proceedings of the 1st Conference on Information-Theoretic Cryptography, 2020

Private Aggregation from Fewer Anonymous Messages.

[BibT_eX]

[DOI]

Proceedings of the Advances in Cryptology - EUROCRYPT 2020, 2020

2019

On the Power of Multiple Anonymous Messages.

[BibT_eX]

[DOI]

IACR Cryptol. ePrint Arch., 2019

Advances and Open Problems in Federated Learning.

[BibT_eX]

[DOI]

Rafael G. L. D'Oliveira

Ananda Theertha Suresh

CoRR, 2019

Private Heavy Hitters and Range Queries in the Shuffled Model.

[BibT_eX]

[DOI]

CoRR, 2019

Scalable and Differentially Private Distributed Aggregation in the Shuffled Model.

[BibT_eX]

[DOI]

Rasmus Pagh

Ameya Velingker

CoRR, 2019

Recursive Sketches for Modular Deep Learning.

[BibT_eX]

[DOI]

Rina Panigrahy

Joshua R. Wang

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Computational aspects of communication amid uncertainty.

[BibT_eX]

[DOI]

PhD thesis, 2018

LP/SDP Hierarchy Lower Bounds for Decoding Random LDPC Codes.

[BibT_eX]

[DOI]

Euiwoong Lee

IEEE Trans. Inf. Theory, 2018

NP-Hardness of Reed-Solomon Decoding, and the Prouhet-Tarry-Escott Problem.

[BibT_eX]

[DOI]

Venkata Gandikota

Elena Grigorescu

SIAM J. Comput., 2018

Communication-Rounds Tradeoffs for Common Randomness and Secret Key Generation.

[BibT_eX]

[DOI]

Electron. Colloquium Comput. Complex., 2018

Communication with Contextual Uncertainty.

[BibT_eX]

[DOI]

Comput. Complex., 2018

2017

The Power of Shared Randomness in Uncertain Communication.

[BibT_eX]

[DOI]

Madhu Sudan

Electron. Colloquium Comput. Complex., 2017

Dimension Reduction for Polynomials over Gaussian Space and Applications.

[BibT_eX]

[DOI]

Pritish Kamath

Prasad Raghavendra

Electron. Colloquium Comput. Complex., 2017

Resource-Efficient Common Randomness and Secret-Key Schemes.

[BibT_eX]

[DOI]

T. S. Jayram

Electron. Colloquium Comput. Complex., 2017

Compression in a Distributed Setting.

[BibT_eX]

[DOI]

Proceedings of the 8th Innovations in Theoretical Computer Science Conference, 2017

On the Power of Learning from k-Wise Queries.

[BibT_eX]

[DOI]

Vitaly Feldman

Proceedings of the 8th Innovations in Theoretical Computer Science Conference, 2017

2016

Decidability of Non-Interactive Simulation of Joint Distributions.

[BibT_eX]

[DOI]

Pritish Kamath

Madhu Sudan

Electron. Colloquium Comput. Complex., 2016

The Optimality of Correlated Sampling.

[BibT_eX]

[DOI]

Electron. Colloquium Comput. Complex., 2016

2015

Communication Complexity of Permutation-Invariant Functions.

[BibT_eX]

[DOI]

Pritish Kamath

Madhu Sudan

Electron. Colloquium Comput. Complex., 2015

On the NP-hardness of bounded distance decoding of Reed-Solomon codes.

[BibT_eX]

[DOI]

Venkata Gandikota

Elena Grigorescu

Proceedings of the IEEE International Symposium on Information Theory, 2015

2014

Linear Programming Decoding of Spatially Coupled Codes.

[BibT_eX]

[DOI]

Louay Bazzi

Rüdiger L. Urbanke

IEEE Trans. Inf. Theory, 2014

The Information Complexity of Hamming Distance.

[BibT_eX]

[DOI]

Eric Blais

Joshua Brody