Faster Rates of Convergence to Stationary Points in Differentially Private Optimization. - Raman Arora; Raef Bassily; Tomás González 002; Cristóbal Guzmán; Michael Menart; Enayat Ullah (ICML, 2023)

Mirror Descent Algorithms with Nearly Dimension-Independent Rates for Differentially-Private Stochastic Saddle-Point Problems extended abstract. - Tomás González 002; Cristóbal Guzmán; Courtney Paquette (COLT, 2024)

Sequentially Auditing Differential Privacy. - Tomás González Lara; Mateo Dulce-Rubio; Aaditya Ramdas; Mónica Ribero (NeurIPS, 2025)

Private Evolution Converges. - Tomás González Lara; Giulia Fanti; Aaditya Ramdas (NeurIPS, 2025)

Vector-valued self-normalized concentration inequalities beyond sub-Gaussianity. - Diego Martinez-Taboada; Tomás González Lara; Aaditya Ramdas (CoRR, 2025)

Mirror Descent Algorithms with Nearly Dimension-Independent Rates for Differentially-Private Stochastic Saddle-Point Problems. - Tomás González 002; Cristóbal Guzmán; Courtney Paquette (SIAM J. Optim., 2026)

Optimal Rates for Differentially Private Hypothesis Testing with E-values. - Ben Jacobsen; Tomás González 002; Gavin Brown; Kassem Fawaz; Aaditya Ramdas (CoRR, 2026)