Marco Avella-Medina

According to our database, Marco Avella-Medina authored at least 15 papers between 2017 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Differentially Private Inference for Longitudinal Linear Regression.

Getoar Sopa, Marco Avella Medina, Cynthia Rush

CoRR, January, 2026

2025

Differential privacy with dependent data.

Valentin Roth, Marco Avella-Medina

CoRR, November, 2025

Scalable Differentially Private Bayesian Optimization.

Getoar Sopa, Juraj Marusic, Marco Avella-Medina, John P. Cunningham

CoRR, February, 2025

Insights into Kernel PCA with Application to Multivariate Extremes.

Marco Avella Medina, Richard A. Davis, Gennady Samorodnitsky

SIAM J. Math. Data Sci., 2025

Differential Privacy Under Class Imbalance: Methods and Empirical Insights.

Lucas Rosenblatt, Yuliia Lut, Ethan Turok, Marco Avella Medina, Rachel Cummings

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

Spectral learning of multivariate extremes.

Marco Avella Medina, Richard A. Davis, Gennady Samorodnitsky

J. Mach. Learn. Res., 2024

Thompson Sampling Itself is Differentially Private.

Tingting Ou, Rachel Cummings, Marco Avella Medina

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Asymptotics for power posterior mean estimation.

Ruchira Ray, Marco Avella-Medina, Cynthia Rush

Proceedings of the 59th Annual Allerton Conference on Communication, 2023

2022

On the Robustness to Misspecification of α-posteriors and Their Variational Approximations.

Marco Avella-Medina, José Luis Montiel Olea, Cynthia Rush, Amilcar Velez

J. Mach. Learn. Res., 2022

Kernel PCA for multivariate extremes.

Marco Avella-Medina, Richard A. Davis, Gennady Samorodnitsky

CoRR, 2022

2021

Differentially private inference via noisy optimization.

Marco Avella-Medina, Casey Bradshaw, Po-Ling Loh

CoRR, 2021

2020

Centrality Measures for Graphons: Accounting for Uncertainty in Networks.

Marco Avella-Medina, Francesca Parise, Michael T. Schaub, Santiago Segarra

IEEE Trans. Netw. Sci. Eng., 2020

Propose, Test, Release: Differentially private estimation with high probability.

Victor-Emmanuel Brunel, Marco Avella-Medina

CoRR, 2020

2019

Privacy-preserving parametric inference: a case for robust statistics.

Marco Avella-Medina

CoRR, 2019

2017

Centrality measures for graphons.

Marco Avella-Medina, Francesca Parise, Michael T. Schaub, Santiago Segarra

CoRR, 2017