| 2026 | ISIT | Optimality of General Staircase Mechanism for Differential Privacy. | James Melbourne, Mario Daz, Shahab Asoodeh |
| 2025 | AISTATS | Locally Private Sampling with Public Data. | Behnoosh Zamanlooy, Mario Daz, Shahab Asoodeh |
| 2025 | ISIT | Tensorization of $f$-Divergences. | Rodrigo Cruz, Mario Daz, Flvio P. Calmon |
| 2025 | ISIT | Auditing Privacy of Additive Noise Mechanisms Using Linear Predictive Models. | Monica Welfert, Nathan Stromberg, Mario Daz, James Melbourne, Lalitha Sankar |
| 2024 | ISIT | On the Privacy Guarantees of Differentially Private Stochastic Gradient Descent. | Shahab Asoodeh, Mario Daz |
| 2024 | ISIT | $\mathrm{E}_{\gamma}$-Mixing Time. | Behnoosh Zamanlooy, Shahab Asoodeh, Mario Daz, Flvio P. Calmon |
| 2023 | ISIT | On the Inevitability of the Rashomon Effect. | Lucas Monteiro Paes, Rodrigo Cruz, Flvio P. Calmon, Mario Daz |
| 2021 | ISIT | The Impact of Split Classifiers on Group Fairness. | Hao Wang, Hsiang Hsu, Mario Daz, Flvio P. Calmon |
| 2021 | ISIT | Neural Network-based Estimation of the MMSE. | Mario Daz, Peter Kairouz, Jiachun Liao, Lalitha Sankar |
| 2020 | ISIT | Privacy Amplification of Iterative Algorithms via Contraction Coefficients. | Shahab Asoodeh, Mario Daz, Flvio P. Calmon |
| 2020 | ISIT | On the α-loss Landscape in the Logistic Model. | Tyler Sypherd, Mario Daz, Lalitha Sankar, Gautam Dasarathy |
| 2019 | ISIT | A Tunable Loss Function for Binary Classification. | Tyler Sypherd, Mario Daz, Lalitha Sankar, Peter Kairouz |
| 2019 | ISIT | An Information-Theoretic View of Generalization via Wasserstein Distance. | Hao Wang, Mario Daz, Jos Cndido Silveira Santos Filho, Flvio P. Calmon |
| 2018 | ISIT | The Utility Cost of Robust Privacy Guarantees. | Hao Wang, Mario Daz, Flvio P. Calmon, Lalitha Sankar |
| 2017 | ISIT | Privacy-aware guessing efficiency. | Shahab Asoodeh, Mario Daz, Fady Alajaji, Tams Linder |
| 2016 | ISIT | On the symmetries and the capacity achieving input covariance matrices of multiantenna channels. | Mario Daz |