Ziv Goldfeld

Orcid: 0000-0003-3406-3950

According to our database1, Ziv Goldfeld authored at least 65 papers between 2012 and 2024.

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Bibliography

2024
Quantum Pufferfish Privacy: A Flexible Privacy Framework for Quantum Systems.
IEEE Trans. Inf. Theory, August, 2024

Limit Distribution Theory for f-Divergences.
IEEE Trans. Inf. Theory, February, 2024

Data-Driven Optimization of Directed Information Over Discrete Alphabets.
IEEE Trans. Inf. Theory, 2024

Robust Distribution Learning with Local and Global Adversarial Corruptions.
CoRR, 2024

Information-Theoretic Generalization Bounds for Deep Neural Networks.
CoRR, 2024

Neural Estimation of Entropic Optimal Transport.
Proceedings of the IEEE International Symposium on Information Theory, 2024

Several Interpretations of Max-Sliced Mutual Information.
Proceedings of the IEEE International Symposium on Information Theory, 2024

Hierarchical Generalization Bounds for Deep Neural Networks.
Proceedings of the IEEE International Symposium on Information Theory, 2024

Robust Distribution Learning with Local and Global Adversarial Corruptions (extended abstract).
Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

2023
Pufferfish Privacy: An Information-Theoretic Study.
IEEE Trans. Inf. Theory, November, 2023

Neural Estimation and Optimization of Directed Information Over Continuous Spaces.
IEEE Trans. Inf. Theory, August, 2023

Quantum Neural Estimation of Entropies.
CoRR, 2023

Robust Estimation under the Wasserstein Distance.
CoRR, 2023

Max-Sliced Mutual Information.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Outlier-Robust Wasserstein DRO.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Limit Distribution Theory for KL divergence and Applications to Auditing Differential Privacy.
Proceedings of the IEEE International Symposium on Information Theory, 2023

2022
Neural Estimation of Statistical Divergences.
J. Mach. Learn. Res., 2022

Statistical, Robustness, and Computational Guarantees for Sliced Wasserstein Distances.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

$k$-Sliced Mutual Information: A Quantitative Study of Scalability with Dimension.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Optimizing Estimated Directed Information over Discrete Alphabets.
Proceedings of the IEEE International Symposium on Information Theory, 2022

Perfect Subset Privacy for Data Sharing and Learning.
Proceedings of the IEEE International Symposium on Information Theory, 2022

An Information-Theoretic Characterization of Pufferfish Privacy.
Proceedings of the IEEE International Symposium on Information Theory, 2022

Cycle Consistent Probability Divergences Across Different Spaces.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Outlier-Robust Optimal Transport: Duality, Structure, and Statistical Analysis.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
The Secrecy Capacity of Cost-Constrained Wiretap Channels.
IEEE Trans. Inf. Theory, 2021

Information Storage in the Stochastic Ising Model.
IEEE Trans. Inf. Theory, 2021

Sliced Mutual Information: A Scalable Measure of Statistical Dependence.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Soft-covering via Constant-composition Superposition codes.
Proceedings of the IEEE International Symposium on Information Theory, 2021

Wiretap Channel with Latent Variable Secrecy.
Proceedings of the IEEE International Symposium on Information Theory, 2021

Smooth p-Wasserstein Distance: Structure, Empirical Approximation, and Statistical Applications.
Proceedings of the 38th International Conference on Machine Learning, 2021

Non-asymptotic Performance Guarantees for Neural Estimation of f-Divergences.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Convergence of Smoothed Empirical Measures With Applications to Entropy Estimation.
IEEE Trans. Inf. Theory, 2020

Wiretap Channels With Random States Non-Causally Available at the Encoder.
IEEE Trans. Inf. Theory, 2020

Key and Message Semantic-Security Over State-Dependent Channels.
IEEE Trans. Inf. Forensics Secur., 2020

The Information Bottleneck Problem and its Applications in Machine Learning.
IEEE J. Sel. Areas Inf. Theory, 2020

Asymptotic Guarantees for Generative Modeling Based on the Smooth Wasserstein Distance.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Limit Distributions for Smooth Total Variation and χ<sup>2</sup>-Divergence in High Dimensions.
Proceedings of the IEEE International Symposium on Information Theory, 2020

Capacity of Continuous Channels with Memory via Directed Information Neural Estimator.
Proceedings of the IEEE International Symposium on Information Theory, 2020

Gaussian-Smoothed Optimal Transport: Metric Structure and Statistical Efficiency.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Wiretap and Gelfand-Pinsker Channels Analogy and Its Applications.
IEEE Trans. Inf. Theory, 2019

MIMO Gaussian Broadcast Channels With Common, Private, and Confidential Messages.
IEEE Trans. Inf. Theory, 2019

Optimality of the Plug-in Estimator for Differential Entropy Estimation under Gaussian Convolutions.
Proceedings of the IEEE International Symposium on Information Theory, 2019

Information Storage in the Stochastic Ising Model at Low Temperature.
Proceedings of the IEEE International Symposium on Information Theory, 2019

Estimating Information Flow in Deep Neural Networks.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
Estimating Information Flow in Neural Networks.
CoRR, 2018

Design of Discrete Constellations for Peak-Power-Limited complex Gaussian Channels.
Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

A Useful Analogy Between Wiretap and Gelfand - Pinsker Channels.
Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

Information Storage in the Stochastic Ising Model at Zero Temperature.
Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

Key-Message Security over State-Dependent Wiretap Channels.
Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

2017
Strong Secrecy for Cooperative Broadcast Channels.
IEEE Trans. Inf. Theory, 2017

Broadcast Channels With Privacy Leakage Constraints.
IEEE Trans. Inf. Theory, 2017

Semantically-Secured Message-Key Trade-off over Wiretap Channels with Random Parameters.
CoRR, 2017

The Gelfand-Pinsker wiretap channel: Higher secrecy rates via a novel superposition code.
Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017

Physical Layer Security over Wiretap Channels with Random Parameters.
Proceedings of the Cyber Security Cryptography and Machine Learning, 2017

2016
Duality of a Source Coding Problem and the Semi-Deterministic Broadcast Channel With Rate-Limited Cooperation.
IEEE Trans. Inf. Theory, 2016

Arbitrarily Varying Wiretap Channels With Type Constrained States.
IEEE Trans. Inf. Theory, 2016

Semantic-Security Capacity for Wiretap Channels of Type II.
IEEE Trans. Inf. Theory, 2016

Fourier-Motzkin Elimination Software for Information Theoretic Inequalities.
CoRR, 2016

Semantic-Security Capacity for the Physical Layer via Information Theory.
Proceedings of the 2016 IEEE International Conference on Software Science, 2016

MIMO Gaussian broadcast channels with common, private and confidential messages.
Proceedings of the 2016 IEEE Information Theory Workshop, 2016

2015
Broadcast channels with cooperation: Capacity and duality for the semi-deterministic case.
Proceedings of the 2015 IEEE Information Theory Workshop, 2015

Cooperative broadcast channels with a secret message.
Proceedings of the IEEE International Symposium on Information Theory, 2015

2014
The Finite State MAC With Cooperative Encoders and Delayed CSI.
IEEE Trans. Inf. Theory, 2014

The Ahlswede-Körner coordination problem with one-sided encoder cooperation.
Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014

2012
Capacity region of the finite state MAC with cooperative encoders and delayed CSI.
Proceedings of the 2012 IEEE International Symposium on Information Theory, 2012


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