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20212025
most citedDimension-Free Rates for Natural Policy Gradient in Multi-Agent Reinforcement Learning

3 citations · 4 across the 6 of their papers we have counts for

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cs.LG2024

Meta-Learning Objectives for Preference Optimization

Carlo Alfano, Silvia Sapora, Jakob Nicolaus Foerster +2

Evaluating preference optimization (PO) algorithms on LLM alignment is a challenging task that presents prohibitive costs, noise, and several variables like model size and hyper-pa…

stat.ML2024

Learning mirror maps in policy mirror descent

Carlo Alfano, Sebastian Towers, Silvia Sapora +2

Policy Mirror Descent (PMD) is a popular framework in reinforcement learning, serving as a unifying perspective that encompasses numerous algorithms. These algorithms are derived t…