Dimension-Free Rates for Natural Policy Gradient in Multi-Agent Reinforcement Learning. - Carlo Alfano; Patrick Rebeschini (CoRR, 2021)

Linear Convergence for Natural Policy Gradient with Log-linear Policy Parametrization. - Carlo Alfano; Patrick Rebeschini (CoRR, 2022)

A Novel Framework for Policy Mirror Descent with General Parameterization and Linear Convergence. - Carlo Alfano; Rui Yuan; Patrick Rebeschini (NeurIPS, 2023)

A Novel Framework for Policy Mirror Descent with General Parametrization and Linear Convergence. - Carlo Alfano; Rui Yuan; Patrick Rebeschini (CoRR, 2023)

Meta-learning the mirror map in policy mirror descent. - Carlo Alfano; Sebastian Towers; Silvia Sapora; Chris Lu 001; Patrick Rebeschini (CoRR, 2024)

Learning Loss Landscapes in Preference Optimization. - Carlo Alfano; Silvia Sapora; Jakob Nicolaus Foerster; Patrick Rebeschini; Yee Whye Teh (CoRR, 2024)

Learning mirror maps in policy mirror descent. - Carlo Alfano; Sebastian Rene Towers; Silvia Sapora; Chris Lu 001; Patrick Rebeschini (ICLR, 2025)

Multilingual Self-Taught Faithfulness Evaluators. - Carlo Alfano; Aymen Al Marjani; Zeno Jonke; Amin Mantrach; Saab Mansour; Marcello Federico (CoRR, 2025)