Shahab Asoodeh

CoRR, 2024

2023

Sample-Optimal Locally Private Hypothesis Selection and the Provable Benefits of Interactivity.

[BibT_eX]

[DOI]

Alireza Fathollah Pour

Hassan Ashtiani

CoRR, 2023

Privacy Loss of Noisy Stochastic Gradient Descent Might Converge Even for Non-Convex Losses.

[BibT_eX]

[DOI]

Mario Díaz

CoRR, 2023

Strong Data Processing Inequalities for Locally Differentially Private Mechanisms.

[BibT_eX]

[DOI]

Behnoosh Zamanlooy

Proceedings of the IEEE International Symposium on Information Theory, 2023

The Cardinality Bound on the Information Bottleneck Representations is Tight.

[BibT_eX]

[DOI]

Etam Benger

Jun Chen

Proceedings of the IEEE International Symposium on Information Theory, 2023

Schrödinger Mechanisms: Optimal Differential Privacy Mechanisms for Small Sensitivity.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2023

Optimal Multidimensional Differentially Private Mechanisms in the Large-Composition Regime.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2023

The Saddle-Point Method in Differential Privacy.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

2022

Contraction of Locally Differentially Private Mechanisms.

[BibT_eX]

[DOI]

Huanyu Zhang

CoRR, 2022

The Saddle-Point Accountant for Differential Privacy.

[BibT_eX]

[DOI]

CoRR, 2022

Beyond Adult and COMPAS: Fairness in Multi-Class Prediction.

[BibT_eX]

[DOI]

CoRR, 2022

Beyond Adult and COMPAS: Fair Multi-Class Prediction via Information Projection.

[BibT_eX]

[DOI]

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

Cactus Mechanisms: Optimal Differential Privacy Mechanisms in the Large-Composition Regime.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2022

Distribution Simulation Under Local Differential Privacy.

[BibT_eX]

[DOI]

Proceedings of the 17th Canadian Workshop on Information Theory, 2022

2021

Three Variants of Differential Privacy: Lossless Conversion and Applications.

[BibT_eX]

[DOI]

IEEE J. Sel. Areas Inf. Theory, 2021

Local Differential Privacy Is Equivalent to Contraction of E<sub>γ</sub>-Divergence.

[BibT_eX]

[DOI]

Maryam Aliakbarpour

CoRR, 2021

Graph Neural Networks for Soft Semi-Supervised Learning on Hypergraphs.

[BibT_eX]

[DOI]

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2021

Differentially Private Federated Learning: An Information-Theoretic Perspective.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2021

Local Differential Privacy Is Equivalent to Contraction of an $f$-Divergence.

[BibT_eX]

[DOI]

Maryam Aliakbarpour

Proceedings of the IEEE International Symposium on Information Theory, 2021

2020

Bottleneck Problems: An Information and Estimation-Theoretic View.

[BibT_eX]

[DOI]

Entropy, 2020

Privacy Analysis of Online Learning Algorithms via Contraction Coefficients.

[BibT_eX]

[DOI]

Mario Díaz

CoRR, 2020

Bottleneck Problems: Information and Estimation-Theoretic View.

[BibT_eX]

[DOI]

CoRR, 2020

Differentially Private Mechanisms for Count Queries.

[BibT_eX]

[DOI]

Parastoo Sadeghi

Flávio du Pin Calmon

CoRR, 2020

A Better Bound Gives a Hundred Rounds: Enhanced Privacy Guarantees via f-Divergences.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2020

Privacy Amplification of Iterative Algorithms via Contraction Coefficients.

[BibT_eX]

[DOI]

Mario Díaz

Karthikeyan Natesan Ramamurthy

Proceedings of the IEEE International Symposium on Information Theory, 2020

Model Projection: Theory and Applications to Fair Machine Learning.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2020

Obfuscation via Information Density Estimation.

[BibT_eX]

[DOI]

Hsiang Hsu

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Estimation Efficiency Under Privacy Constraints.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Theory, 2019

Information-Theoretic Privacy Watchdogs.

[BibT_eX]

[DOI]

Hsiang Hsu

Proceedings of the IEEE International Symposium on Information Theory, 2019

Wasserstein Soft Label Propagation on Hypergraphs: Algorithm and Generalization Error Bounds.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

On the Noise-Information Separation of a Private Principal Component Analysis Scheme.

[BibT_eX]

[DOI]

Serban Teodor Belinschi

James A. Mingo

CoRR, 2018

Generalizing Bottleneck Problems.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

A Tamper-Free Semi-Universal Communication System for Deletion Channels.

[BibT_eX]

[DOI]

Yi Huang

Ishanu Chattopadhyay

Proceedings of the 57th IEEE Conference on Decision and Control, 2018

Curvature of Hypergraphs via Multi-Marginal Optimal Transport.

[BibT_eX]

[DOI]

Tingran Gao

James Evans

Proceedings of the 57th IEEE Conference on Decision and Control, 2018

2017

Privacy-aware guessing efficiency.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017

2016

Information Extraction Under Privacy Constraints.

[BibT_eX]

[DOI]

Inf., 2016

Privacy-aware MMSE estimation.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2016

Almost Perfect Privacy for Additive Gaussian Privacy Filters.

[BibT_eX]

[DOI]

Proceedings of the Information Theoretic Security - 9th International Conference, 2016

2015

On maximal correlation, mutual information and data privacy.

[BibT_eX]

[DOI]

Proceedings of the 14th IEEE Canadian Workshop on Information Theory, 2015

Lossless secure source coding: Yamamoto's setting.

[BibT_eX]

[DOI]

Proceedings of the 53rd Annual Allerton Conference on Communication, 2015

2014

Notes on information-theoretic privacy.

[BibT_eX]

[DOI]

Proceedings of the 52nd Annual Allerton Conference on Communication, 2014

2013

An achievability proof for the lossy coding of Markov sources with feed-forward.

[BibT_eX]

[DOI]

Proceedings of the 13th Canadian Workshop on Information Theory, 2013

2010

It takes half the energy of a photon to send one bit reliably on the Poisson channel with feedback

[BibT_eX]

[DOI]

Amos Lapidoth

Ligong Wang

CoRR, 2010

New stopping criterion for turbo code in the presence of SNR mismatch.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Ultra Modern Telecommunications, 2010

2007

A novel algorithm for CFO estimation in OFDM-based systems.

[BibT_eX]

Alireza Rezazade

Proceedings of the Sixth IASTED International Conference on Communications, 2007

On power control in cellular communication using ANFIS.

[BibT_eX]