Nicholas Corrado

According to our database, Nicholas Corrado authored at least 7 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

When Can Model-Free Reinforcement Learning be Enough for Thinking?

Josiah P. Hanna, Nicholas E. Corrado

CoRR, June, 2025

AutoMixAlign: Adaptive Data Mixing for Multi-Task Preference Optimization in LLMs.

Nicholas E. Corrado, Julian Katz-Samuels, Adithya M. Devraj, Hyokun Yun, Chao Zhang, Yi Xu, Yi Pan, Bing Yin, Trishul Chilimbi

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024

Guided Data Augmentation for Offline Reinforcement Learning and Imitation Learning.

Nicholas E. Corrado, Yuxiao Qu, John U. Balis, Adam Labiosa, Josiah P. Hanna

RLJ, 2024

Understanding when Dynamics-Invariant Data Augmentations Benefit Model-free Reinforcement Learning Updates.

Nicholas Corrado, Josiah P. Hanna

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

On-Policy Policy Gradient Reinforcement Learning Without On-Policy Sampling.

Nicholas E. Corrado, Josiah P. Hanna

CoRR, 2023

Deep Reinforcement Learning for Distribution Power System Cyber-Resilience via Distributed Energy Resource Control.

Nicholas E. Corrado, Michael Livesay, Tyson Bailey, Jay Johnson, Drew Levin

Proceedings of the IEEE International Conference on Communications, 2023

2022

Simulation-Acquired Latent Action Spaces for Dynamics Generalization.

Nicholas Corrado, Yuxiao Qu, Josiah P. Hanna

Proceedings of the Conference on Lifelong Learning Agents, 2022