On the Compressibility of Affinely Singular Random Vectors. - Mohammad-Amin Charusaie; Stefano Rini; Arash Amini (ISIT, 2020)

Polynomial magic! Hermite polynomials for private data generation. - Mijung Park; Margarita Vinaroz; Mohammad-Amin Charusaie; Frederik Harder (CoRR, 2021)

Sample Efficient Learning of Predictors that Complement Humans. - Mohammad-Amin Charusaie; Hussein Mozannar; David A. Sontag; Samira Samadi (ICML, 2022)

Hermite Polynomial Features for Private Data Generation. - Margarita Vinaroz; Mohammad-Amin Charusaie; Frederik Harder; Kamil Adamczewski; Mijung Park (ICML, 2022)

Compressibility Measures for Affinely Singular Random Vectors. - Mohammad-Amin Charusaie; Arash Amini; Stefano Rini (IEEE Trans. Inf. Theory, 2022)

A Unifying Post-Processing Framework for Multi-Objective Learn-to-Defer Problems. - Mohammad-Amin Charusaie; Samira Samadi (NeurIPS, 2024)

ARMA Processes With Discrete-Continuous Excitation: Compressibility Beyond Sparsity. - Mohammad-Amin Charusaie; Arash Amini; Stefano Rini (IEEE Trans. Inf. Theory, 2025)