Mario Díaz

Orcid: 0000-0002-9321-9815

According to our database¹, Mario Díaz authored at least 25 papers between 2014 and 2023.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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PhD thesis

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Bibliography

2023

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

[BibT_eX]

[DOI]

Shahab Asoodeh

Mario Díaz

CoRR, 2023

On the Inevitability of the Rashomon Effect.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2023

2022

A Tunable Loss Function for Robust Classification: Calibration, Landscape, and Generalization.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Theory, 2022

2021

To Split or not to Split: The Impact of Disparate Treatment in Classification.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Theory, 2021

Lower Bounds for the Minimum Mean-Square Error via Neural Network-based Estimation.

[BibT_eX]

[DOI]

Mario Díaz

Peter Kairouz

Lalitha Sankar

CoRR, 2021

Neural Network-based Estimation of the MMSE.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2021

The Impact of Split Classifiers on Group Fairness.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2021

2020

On the Robustness of Information-Theoretic Privacy Measures and Mechanisms.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Theory, 2020

Privacy Analysis of Online Learning Algorithms via Contraction Coefficients.

[BibT_eX]

[DOI]

Shahab Asoodeh

Mario Díaz

Flávio P. Calmon

CoRR, 2020

On the alpha-loss Landscape in the Logistic Model.

[BibT_eX]

[DOI]

CoRR, 2020

On the α-loss Landscape in the Logistic Model.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2020

Privacy Amplification of Iterative Algorithms via Contraction Coefficients.

[BibT_eX]

[DOI]

Shahab Asoodeh

Mario Díaz

Flávio P. Calmon

Proceedings of the IEEE International Symposium on Information Theory, 2020

2019

Estimation Efficiency Under Privacy Constraints.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Theory, 2019

Theoretical Guarantees for Model Auditing with Finite Adversaries.

[BibT_eX]

[DOI]

CoRR, 2019

A Tunable Loss Function for Classification.

[BibT_eX]

[DOI]

CoRR, 2019

An Information-Theoretic View of Generalization via Wasserstein Distance.

[BibT_eX]

[DOI]

Hao Wang

Mario Díaz

José Cândido Silveira Santos Filho

Flávio P. Calmon

Proceedings of the IEEE International Symposium on Information Theory, 2019

A Tunable Loss Function for Binary Classification.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2019

2018

On the Contractivity of Privacy Mechanisms.

[BibT_eX]

[DOI]

Mario Díaz

Lalitha Sankar

Peter Kairouz

CoRR, 2018

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

[BibT_eX]

[DOI]

Serban Teodor Belinschi

James A. Mingo

CoRR, 2018

The Utility Cost of Robust Privacy Guarantees.

[BibT_eX]

[DOI]

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

2017

On the Capacity of Block Multiantenna Channels.

[BibT_eX]

[DOI]

Mario Díaz

Víctor Pérez-Abreu

IEEE Trans. Inf. Theory, 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

On the symmetries and the capacity achieving input covariance matrices of multiantenna channels.

[BibT_eX]

[DOI]

Mario Díaz

Proceedings of the IEEE International Symposium on Information Theory, 2016

2014

On the Asymptotic Ergodic Capacity of Correlated Multiantenna Channels using Finite Dimensional Statistics.

[BibT_eX]

[DOI]

Mario Díaz

Víctor Pérez-Abreu

CoRR, 2014

Mario Díaz

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