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Nicholas Corrado

Nicholas E. Corrado

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2020 – today

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2024
[c3]
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  - conf/iclr/CorradoH24
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Nicholas Corrado, Josiah P. Hanna:
Understanding when Dynamics-Invariant Data Augmentations Benefit Model-free Reinforcement Learning Updates. ICLR 2024
2023
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  - conf/smartgridcomm/CorradoLBJL23
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Nicholas E. Corrado, Michael Livesay, Tyson Bailey, Jay Johnson, Drew Levin:
Deep Reinforcement Learning for Distribution Power System Cyber-Resilience via Distributed Energy Resource Control. SmartGridComm 2023: 1-6
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  - journals/corr/abs-2310-17786
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Nicholas E. Corrado, Josiah P. Hanna:
Understanding when Dynamics-Invariant Data Augmentations Benefit Model-Free Reinforcement Learning Updates. CoRR abs/2310.17786 (2023)
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  - journals/corr/abs-2310-18247
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Nicholas E. Corrado, Yuxiao Qu, John U. Balis, Adam Labiosa, Josiah P. Hanna:
Guided Data Augmentation for Offline Reinforcement Learning and Imitation Learning. CoRR abs/2310.18247 (2023)
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  - journals/corr/abs-2311-08290
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Nicholas E. Corrado, Josiah P. Hanna:
On-Policy Policy Gradient Reinforcement Learning Without On-Policy Sampling. CoRR abs/2311.08290 (2023)
2022
[c1]
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  - conf/collas/CorradoQH22
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Nicholas Corrado, Yuxiao Qu, Josiah P. Hanna:
Simulation-Acquired Latent Action Spaces for Dynamics Generalization. CoLLAs 2022: 661-682

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