James Queeney
![James Queeney](/public/img/photography/people/queeney.jpg)
- Phone: 617-621-7511
- Email:
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Position:
Research / Technical Staff
Postdoctoral Research Fellow -
Education:
Ph.D., Boston University, 2023 -
Research Areas:
External Links:
Jimmy's Quick Links
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Biography
Jimmy conducts research on data-driven methods for decision making and control. During his PhD, he developed reliable deep reinforcement learning algorithms with guarantees on training stability, robustness, and safety.
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MERL Publications
- "Visually Robust Adversarial Imitation Learning from Videos with Contrastive Learning", arXiv, June 2024. ,
- "Adversarial Imitation Learning from Visual Observations using Latent Information", Transactions on Machine Learning Research (TMLR), June 2024.BibTeX TR2024-068 PDF
- @article{Giammarino2024jun,
- author = {Giammarino, Vittorio and Queeney, James and Paschalidis, Ioannis Ch.},
- title = {Adversarial Imitation Learning from Visual Observations using Latent Information},
- journal = {Transactions on Machine Learning Research (TMLR)},
- year = 2024,
- month = jun,
- issn = {2835-8856},
- url = {https://www.merl.com/publications/TR2024-068}
- }
, - "Provably Efficient Off-Policy Adversarial Imitation Learning with Convergence Guarantees", arXiv, May 2024.BibTeX arXiv
- @article{Chen2024may2,
- author = {Chen, Yilei and Giammarino, Vittorio and Queeney, James and Paschalidis, Ioannis Ch.}},
- title = {Provably Efficient Off-Policy Adversarial Imitation Learning with Convergence Guarantees},
- journal = {arXiv},
- year = 2024,
- month = may,
- url = {https://arxiv.org/abs/2405.16668}
- }
, - "Optimal Transport Perturbations for Safe Reinforcement Learning with Robustness Guarantees", Transactions on Machine Learning Research (TMLR), April 2024.BibTeX TR2024-037 PDF
- @article{Queeney2024apr,
- author = {Queeney, James and Ozcan, Erhan Can and Paschalidis, Ioannis Ch. and Cassandras, Christos G.},
- title = {Optimal Transport Perturbations for Safe Reinforcement Learning with Robustness Guarantees},
- journal = {Transactions on Machine Learning Research (TMLR)},
- year = 2024,
- month = apr,
- issn = {2835-8856},
- url = {https://www.merl.com/publications/TR2024-037}
- }
, - "A Model-Based Approach for Improving Reinforcement Learning Efficiency Leveraging Expert Observations", arXiv, February 2024.BibTeX arXiv
- @article{Ozcan2024feb,
- author = {Ozcan, Erhan Can and Giammarino, Vittorio and Queeney, James and Paschalidis, Ioannis Ch.},
- title = {A Model-Based Approach for Improving Reinforcement Learning Efficiency Leveraging Expert Observations},
- journal = {arXiv},
- year = 2024,
- month = feb,
- url = {https://arxiv.org/abs/2402.18836}
- }
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Other Publications
- "Opportunities and Challenges from Using Animal Videos in Reinforcement Learning for Navigation", 22nd IFAC World Congress, 2023.BibTeX
- @Inproceedings{giammarino_2023_ifac,
- author = {Giammarino, Vittorio and Queeney, James and Carstensen, Lucas C. and Hasselmo, Michael E. and Paschalidis, Ioannis Ch.},
- title = {Opportunities and Challenges from Using Animal Videos in Reinforcement Learning for Navigation},
- booktitle = {22nd IFAC World Congress},
- year = 2023
- }
, - "Adversarial Imitation Learning from Visual Observations using Latent Information", 2023.BibTeX
- @Misc{giammarino_2023_laifo,
- author = {Giammarino, Vittorio and Queeney, James and Paschalidis, Ioannis Ch.},
- title = {Adversarial Imitation Learning from Visual Observations using Latent Information},
- year = 2023
- }
, - "Reliable Deep Reinforcement Learning: Stable Training and Robust Deployment", 2023, Boston University.BibTeX
- @Phdthesis{queeney_2023_dissertation,
- author = {Queeney, James},
- title = {Reliable Deep Reinforcement Learning: Stable Training and Robust Deployment},
- school = {Boston University},
- year = 2023
- }
, - "Optimal Transport Perturbations for Safe Reinforcement Learning with Robustness Guarantees", 2023.BibTeX
- @Misc{queeney_2023_otp,
- author = {Queeney, James and Ozcan, Erhan Can and Paschalidis, Ioannis Ch. and Cassandras, Christos G.},
- title = {Optimal Transport Perturbations for Safe Reinforcement Learning with Robustness Guarantees},
- year = 2023
- }
, - "Risk-Averse Model Uncertainty for Distributionally Robust Safe Reinforcement Learning", Advances in Neural Information Processing Systems, 2023, vol. 36.BibTeX
- @Inproceedings{queeney_2023_ramu,
- author = {Queeney, James and Benosman, Mouhacine},
- title = {Risk-Averse Model Uncertainty for Distributionally Robust Safe Reinforcement Learning},
- booktitle = {Advances in Neural Information Processing Systems},
- year = 2023,
- volume = 36,
- publisher = {Curran Associates, Inc.}
- }
, - "Generalized Policy Improvement Algorithms with Theoretically Supported Sample Reuse", 2022.BibTeX
- @Misc{queeney_2022_gpi,
- author = {Queeney, James and Paschalidis, Ioannis Ch. and Cassandras, Christos G.},
- title = {Generalized Policy Improvement Algorithms with Theoretically Supported Sample Reuse},
- year = 2022
- }
, - "Generalized Proximal Policy Optimization with Sample Reuse", Advances in Neural Information Processing Systems, 2021, vol. 34.BibTeX
- @Inproceedings{queeney_2021_geppo,
- author = {Queeney, James and Paschalidis, Ioannis Ch. and Cassandras, Christos G.},
- title = {Generalized Proximal Policy Optimization with Sample Reuse},
- booktitle = {Advances in Neural Information Processing Systems},
- year = 2021,
- volume = 34,
- publisher = {Curran Associates, Inc.}
- }
, - "Uncertainty-Aware Policy Optimization: A Robust, Adaptive Trust Region Approach", Proceedings of the AAAI Conference on Artificial Intelligence, 2021, vol. 35, pp. 9377-9385.BibTeX
- @Inproceedings{queeney_2021_uatrpo,
- author = {Queeney, James and Paschalidis, Ioannis Ch. and Cassandras, Christos G.},
- title = {Uncertainty-Aware Policy Optimization: A Robust, Adaptive Trust Region Approach},
- booktitle = {Proceedings of the {AAAI} Conference on Artificial Intelligence},
- year = 2021,
- volume = 35,
- pages = {9377--9385},
- publisher = {{AAAI} Press}
- }
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- "Opportunities and Challenges from Using Animal Videos in Reinforcement Learning for Navigation", 22nd IFAC World Congress, 2023.