19 citations · 37 across the 10 of their papers we have counts for
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cs.LG2024
Multi-Armed Bandit Approach for Optimizing Training on Synthetic Data
Abdulrahman Kerim, Leandro Soriano Marcolino, Erickson R. Nascimento +1
Supervised machine learning methods require large-scale training datasets to perform well in practice. Synthetic data has been showing great progress recently and has been used as…
cs.LG2022★ 2 cited
Certified Policy Smoothing for Cooperative Multi-Agent Reinforcement Learning
Ronghui Mu, Wenjie Ruan, Leandro Soriano Marcolino +2
Cooperative multi-agent reinforcement learning (c-MARL) is widely applied in safety-critical scenarios, thus the analysis of robustness for c-MARL models is profoundly important. H…