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Publications

Preprints

Authors

  1. Jonathan Fried, Santiago Paternain, ’'A Bi-Level Optimization Method for Redundant Dual-Arm Minimum Time Problem’’, IEEE Control Systems Letters (submitted March 2025).

  2. Halil Yigit Oksuz, Santiago Paternain, and Joerg Raisch, ’'Deterministic Privacy in Robust Federated Learning through Subgradient Scaling’’, IEEE Control Systems Letters (submitted March 2025).

  3. Jushan Chen, Santiago Paternain, ’'Learning Closed-Loop Parametric Nash Equilibria of Multi-Agent Collaborative Field Coverage’’, IEEE Control Systems Letters (submitted March 2025).

  4. Soham Das, Santiago Paternain, Luiz F. O. Chamon and Ceyhun Eksin ’'The Lagrangian Method for Solving Constrained Markov Games’’, IEEE Transactions on Automatic Control (submitted in March 2025).

  5. Damsara Jayarathne, Santiago Paternain, Sandipan Mishra, ‘‘Combining Model-based Control and Reinforcement Learning for Autonomous Helicopter Aerial Refueling’’, Journal on Dynamical Systems, Measurement and Control (submitted March 2025).

  6. Jonathan Light, Wei Cheng, Yue Wu, Masafumi Oyamada, Mengdi Wang, Santiago Paternain, Haifeng Chen ‘‘DISC: Dynamic Decomposition Improves LLM Inference Scaling,’’ submitted to the 2025 International Conference on Machine Learning.

  7. Leopoldo Agorio, Sean Van Alen, Santiago Paternain, Miguel Calvo-Fullana, Juan Bazerque, ’'Cooperative Multi-Agent Assignment over Stochastic Graphs via Constrained Reinforcement Learning’’, IEEE Transactions on Automatic Control(submitted in February 2025).

  8. Jonathan Fried, Santiago Paternain, ‘‘A Bi-Level Optimization Approach to Joint Trajectory Optimization for Redundant Manipulators’’, IEEE Transactions on Automatic Control (submitted in November 2024).

  9. Clark Zhang, Santiago Paternain , and Alejandro Ribeiro. “Sufficiently Accurate Model Learning for Planning”, IEEE Robotic Letters. February 2021 (Under Review)

  10. Bruno A. Angélico, Luiz F.O. Chamon, Santiago Paternain , Daniel Mox, Alejandro Ribeiro and George J. Pappas. “Gradient Free Source Seeking in Spherical Worlds with Convex Obstacles”, IEEE Transactions on Mechatronics. March 2020 (Under Review)

  11. Santiago Paternain , Manfred Morari and Alejandro Ribeiro. “A Prediction-Correction Algorithm for Real-Time Model Predictive Control”, IEEE Transactions on Automatic Control. November 2019 (Under Review)

Journals

  1. Weiqin Chen,Santiago Paternain, ‘‘SAD: State-Action Distillation for In-Context Reinforcement Learning under Random Policies’’, Transaction on Machine Learning (Accepted April 2025).

  2. Honglu He, Chen-lung Lu, Glenn Saunders, Pinghai Yang, Jeffrey Schoonover, John Wason, Santiago Paternain, Agung Julius, and John T. Wen. “Fast and Accurate Relative Motion Tracking for Two Industrial Robots,” IEEE Robotics and Automation Letters. Submitted April 2024 (Accepted).

  3. Anmol Dwivedi, Santiago Paternain and Ali Tajer “Blackout Mitigation via Physics-guided RL”, IEEE Transactions on Power Systems, Submitted January 2024 (Accepted).

  4. Glory Justin, Santiago Paternain, “Real-Time Small-Signal Security Assessment Using Graph Neural Networks”, Sustainable Energy, Grids and Networks Journal, vol. 39, Art no. 101469, September. 2024, doi: 10.1016/j.segan.2024.101469.

  5. Sergio Rozada, Santiago Paternain, Antonio G. Marques “Tensor and Matrix Low-Rank Value-Function Approximation in Reinforcement Learning”, IEEE Transactions on Signal Processing, vol: 72, issue:, 2024 pp. 1634-1649, March 2024.

  6. Weiqin Chen, Dharmashankar Subramanian, Santiago Paternain. “Probabilistic Constraint for Safety-Critical Reinforcement Learning”, IEEE Transactions on Automatic Control, vol: 69, issue: 10, October 2024 pp. 6789-6804..

  7. Miguel Calvo-Fullana, Santiago Paternain, Luiz F.O. Chamon and Alejandro Ribeiro. “State Augmented Constrained Reinforcement Learning: Overcoming the Limitations of Learning with Rewards”, IEEE Transactions on Automatic Control, vol: 68, issue: 7, July 2024, pp. 4275-4290.

  8. Santiago Paternain , Miguel Calvo-Fullana, Luiz F.O. Chamon and Alejandro Ribeiro. “Safe Policies for Reinforcement Learning Via Primal-Dual methods”, IEEE Transactions on Automatic Control, vol: 68, issue: 3, March 2023, pp. 1321–1336.

  9. Harshat Kumar, Santiago Paternain and Alejandro Ribeiro. “Navigation of a Quadratic Potential with Ellipsoidal Obstacles”, Automatica, December 2022, pp. 110643

  10. Luiz F.O. Chamon, Santiago Paternain, Miguel Calvo-Fullana and Alejandro Ribeiro. “Constrained Learning with Non-Convex Losses”, IEEE Transactions on Information Theory, vol:69, issue:9, March 2023, pp 1739-1760.

  11. Santiago Paternain , Juan Andrés Bazerque and Alejandro Ribeiro. “Policy Gradient for Continuing Tasks in Discounted Markov Decision Processes”, IEEE Transactions on Automatic Control, vol:67, issue:9 September 2022, pp 4467–4482.

  12. Santiago Paternain , Juan Andrés Bazerque, Austin Small and Alejandro Ribeiro. “Stochastic Policy Gradient Ascent in Reproducing Kernel Hilbert Spaces”, IEEE Transactions on Automatic Control, vol:66, issue:8 August 2021, pp 3429–3444.

  13. Andrea Simonetto, Emiliano Dall'Anese, Santiago Paternain , Geert Leus and Georgios B. Giannakis. “Time-Varying Convex Optimization: Time-Structured Algorithms and Applications”, IEEE Proceedings of the IEEE vol:108, issue:11, November 2020 pp. 2032–2048.

  14. Santiago Paternain , Soomin Lee, Michael M. Zavlanos and Alejandro Ribeiro. “Distributed Constrained Online Learning”, IEEE Transactions on Signal Processing vol:68, issue: 6, June 2020, pp. 3486 - 3499.

  15. Maria Peifer, Luiz F.O. Chamon, Santiago Paternain and Alejandro Ribeiro. “Sparse Multi- resolution representations with Adaptive Kernels”, IEEE Transactions on Signal Processing, vol:68, February 2020, pp.2031-2044.

  16. Santiago Paternain and Alejandro Ribeiro. “Stochastic Artificial Potentials for Online Safe Navigation”, IEEE Transactions on Automatic Control, vol: 65, issue: 5, May 2020,pp.1985–2000.

  17. Santiago Paternain , Aryan Mokhtari and Alejandro Ribeiro. “A Newton-Based Method for Nonconvex Optimization with Fast Evasion of Saddle Points”, SIAM, Journal on Optimization, vol:29,No.1 January 2019, pp.343-368.

  18. Santiago Paternain, Daniel E. Koditschek and Alejandro Ribeiro. “Navigation Functions for Convex Potentials in a Space with Convex Obstacles”, IEEE Transactions on Automatic Control, vol:63, issue: 9 September 2018 p.2944-2959.

  19. Mahyar Fazlyab, Santiago Paternain , Victor M. Preciado and Alejandro Ribeiro.“Prediction- Correction Interior-Point Method for Time-Varying Convex Optimization”, IEEE Transactions on Automatic Control, vol:63, issue: 7 July 2018 p.1973-1986.

  20. Alec Koppel, Santiago Paternain , Cedric Richard and Alejandro Ribeiro. “Decentralized Online Learning with Kernels”, IEEE Transactions on Signal Processing, vol:66, issue: 12 June 2018 p.3240-3255.

  21. Santiago Paternain and Alejandro Ribeiro. “Online Learning of Feasible Strategies in Unknown Environments”, IEEE Transactions on Automatic Control, vol:62, issue:6 June 2017 p.2807- 2822.

Conferences

  1. Martin Randall, Santiago Paternain, Pedro Casas, Federico Larroca, Pablo Belzarena, “User Association in Wireless Networks with Distributed GNN-Based Reinforcement Learning”, In Proceedings of the 12th IFIP International Conference on New Technologies, Mobility and Security, pp. (to appear) June 18–20, Paris, France.

  2. Honglu He, Chen-lung Lu, Glenn Saunders, Pinghai Yang, Jeffrey Schoonover, John Wason, Santiago Paternain, Agung Julius, and John T. Wen. ‘‘Fast and Accurate Relative Motion Tracking for Two Industrial Robots,’’ In Proceedings of the 2025 IEEE International Conference on Robotics and Automation (ICRA), pp. (to appear) May 19-23, 2025, Atlanta, GA.

  3. Shima Rabiei, Sandipan Mishra, Santiago Paternain, “Transfer Learning for a Class of Cascade Dynamical Systems”,In Proc. 2025 American Control Conference, pp. (to appear), Denver, CO July 8-10.

  4. Damsara Jayarathne, bf Santiago Paternain, Sandipan Mishra, ‘‘Autonomous helicopter aerial refueling: controller design and performance guarantees’'In Proc. 2025 American Control Conference, pp. (to appear), Denver, CO July 8-10.

  5. Weiqin Chen, Santiago Paternain, “Random Policy Enables In-Context Reinforcement Learning within Trust Horizon”, 8th Workshop on Generalization in Planning (GenPlan) at AAAI 2025.

  6. Weiqin Chen, Mark S. Squillante, Chai-Wah, Wu, Santiago Paternain, “A General Control-Theoretic Approach for Reinforcement Learning: Theory and Algorithms”. 39th Annual AAAI Conference on Artificial Intelligence 2025 Workshop on Combining AI and OR/MS for Better Trustworthy Decision Making.

  7. Sergio Rozada, textbf{Santiago Paternain}, Juan Andrés Bazarque, Antonio G. Marquez, ‘‘A Tensor Low-Rank Approximation for Value Functions in Multi-Task Reinforcement Learning’’, In proceedings of ‘‘58th Asilomar Conference on Signals, Systems, and Computers’’, Asilomar 27–30 October, 2024. pp.

  8. Anmol Dwivedi, Santiago Paternain, Nurali Virali and Ali Tajer “Reinforcement Learning for Mitigating Cascading Failures: Targeted Exploration via Sensitivity Factors”, CCAI's Tackling Climate Change with Machine Learning workshop at NeurIPS 2024, Vancouver, Canada, December 15.

  9. Glory Justin, Santiago Paternain, “Graph Neural Networks for Power System Security Assessment”, In Proceedings of 3rd International Conference on Power Systems and Electrical Technology, Tokyo, Japan, August 5-8. (to appear).

  10. Leopoldo Agorio, Sean Van Alen, Miguel Calvo-Fullana, Santiago Paternain and Juan Andrés Bazerque, “Multi-agent assignment via state augmented reinforcement learning”, Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1202-1213, Oxford, UK, July 15-17.

  11. Weiqin Chen and Santiago Paternain “Generalized Safe Reinforcement Learning”, Proceedings of the 6th Annual Learning for Dynamics & Control Conference, PMLR 242:1606-1618 , Oxford, UK July 15-17.

  12. Jonathan Fried and Santiago Paternain, “Joint Trajectory Optimization for Redundant Manipulators with Constant Path Speed”, In Proc. 2024 American Control Conference, Toronto, Canada July 10-12 pp. 3833-3840.

  13. Damsara Jayarathne, Santiago Paternain, Sandipan Mishra “Allocation of Control Authority Between Dynamic Inversion and Reinforcement Learning for Autonomous Helicopter Aerial Refueling”, In Proc. 2024 American Control Conference, pp. 2386-2392, Toronto, Canada July 10-12.

  14. Weiqin Chen, James Onyejizu, Long Vu, Lan Hoang, Dharmashankar Subramanian, Koushik Kar, Sandipan Mishra and Santiago Paternain, “Adaptive Primal-Dual Method for Safe Reinforcement Learning”, In The 23rd International Conference on Autonomous Agents and Multi-Agent Systems, pp. 326-334, Auckland, New Zeland, May 6-102024.

  15. Han Shen, Santiago Paternain, Gaowen Liu, Ramana Kompella, Tianyi Chen “A Method for Bilevel Optimization with Convex Lower-level Problem”, In Proc. 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 9426-9430. Seoul, Korea April 14–19 2024.

  16. Arindam Chowdhury, Santiago Paternain, Gunjan Verma, Ananthram Swami and Santiago Segarra “Learning Non-myopic Power Allocation in Constrained Scenarios”, In Proc. IEEE Asilomar Conference on Signals, Systems and Computers, pp. 804-808 , Pacific Grove, CA, October 29-November 1 2023.

  17. Damsara Jayarathne, Santiago Paternain, Sandipan Mishra “Safe Residual Reinforcement Learning for Helicopter Aerial Refueling,” 2023 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), pp. 263-269 Seattle, WA June 27–July 1st, 2023.

  18. Weiqin Chen, Darmashankar Subramanian and Santiago Paternain, “Policy Gradients for Probabilistic Constrained Reinforcement Learning,” 57th Annual Conference on Information Sciences and Systems (CISS), pp. 1-6, Baltimore, MD, USA, March 22-24, 2023.

  19. Miguel Calvo-Fullana, Santiago Paternain, Luiz FO. Chamon and Alejandro Ribeiro. “State Augmented Constrained Reinforcement Learning: Overcoming the Limitations of Learning with Rewards”. 33rd Conference on Neural Information Processing Systems, workshop on Safe and Robust Control of Uncertain Systems. Virtual conference, December 6–14,2021.

  20. Miguel-Calvo-Fullana, Luiz F.O. Chamon and Santiago Paternain. “Towards Safe Continuing Task Reinforcement Learning” In Proc. 2021 American Control Conference, pp. 902-908. New Orleands, LA, May 26–28, 2021.

  21. Bruno Angelico, Luiz F. O. Chamon, Santiago Paternain, Alejandro Ribeiro, George J. Pappas.“Source Seeking in Unknown Environments with Convex Obstacles”. In Proc. 2021 American Control Conference, pp. 5055-5061. New Orleands, LA, May 26–28, 2021.

  22. Luiz F.O. Chamon,Santiago Paternain , Alexandre Amice and Alejandro Ribeiro. “Resilient Control: Compromising to Adapt”, In Proc. 58th Conference on Decision and Control, pp. 5703-5710. Jeju, Korea, December 8-11,2020.

  23. Luiz F.O. Chamon, Santiago Paternain , Miguel Calvo-Fullana and Alejandro Ribeiro. “The Empirical Duality Gap of Constrained Statistical Learning”. In Proc. 45th International Conference on Acoustics, Speech, and Signal Processing, Barcelona, pp. 8474-8378. Spain, May 4-8 2020. (Best Student Paper Award) .

  24. Harshat Kumar, Santiago Paternain and Alejandro Ribeiro. “Navigation of a QuadraticPotential with Star Obstacles”. In Proc. 2020 American Control Conference pp. 2043-2048. Denver, Colorado, July 1-3 2020.

  25. Clark Zhang, Arbaaz Khan, Santiago Paternain and Alejandro Ribeiro. “Sufficiently Accurate Model Learning”. In Proc. 2020 International Conference on Robotics and Automation, 10991-10997. Paris, France, May 31-June 4,2020.

  26. Luiz F.O. Chamon, Santiago Paternain and Alejandro Ribeiro. “Counterfactual Programming for Optimal Control”. In Proc. Learning for Dynamics and Control, vol. 120, pp. 235-244, Berkley, CA, June 10-11 2020.

  27. Santiago Paternain , Miguel Calvo-Fullana, Luiz F.O. Chamon and Alejandro Ribeiro. “Constrained Reinforcement Learning Has Zero Duality Gap.” In Proc. 33rd Conference on Neural Information Processing Systems, vol. 7553-7563. Vancouver, Canada, December 8-14,2019.

  28. Santiago Paternain , Miguel Calvo-Fullana, Luiz F.O. Chamon and Alejandro Ribeiro. “Learning Safe Policies Via Primal-Dual methods.” In Proc. 58th Conference on Decision and Control, 6491-6497. Nice, France, December 11-13,2019.

  29. Santiago Paternain, Manfred Morari and Alejandro Ribeiro. “Real-Time Model Predictive Control Based on Prediction-Correction Algorithms”, In Proc. 58th Conference on Decision and Control, vol. 5285-5291. Nice, France, December 11-13,2019. (Invited Session)

  30. Santiago Paternain , Juan Andrés Bazerque, Austin Small and Alejandro Ribeiro. “Policy Improvement Directions for Reinforcement Learning in Reproducing Kernel Hilbert Spaces.” In Proc. 58th Conference on Decision and Control, 7454-7461. Nice France, December 11-13,2019.

  31. Santiago Paternain , Soomin Lee, Michael M. Zavlanos and Alejandro Ribeiro. “Constrained Online Learning in Networks with Sublinear Regret and Fit”, In Proc. 58th Conference on Decision and Control, vol. 5486-5493. Nice, France, December 11-13,2019.

  32. Harshat Kumar,Santiago Paternain and Alejandro Ribeiro. “Navigation of Quadratic Potentials with Ellipsoidal Obstacles”, In Proc. 58th Conference on Decision and Control, vol. 4777-4784. Nice, France, December 11-13,2019.

  33. Luiz F.O. Chamon, Santiago Paternain and Alejandro Ribeiro. “Bayesian Model Learning for Gaussian Processes: Optimizing your way to a posterior”. In Proc. IEEE Asilomar Conference on Signals, Systems and Computers, vol. 482-486, Paciffic Grove, CA, November 3-6 2019.

  34. Santiago Paternain , Mahyar Fazlyab, Victor M. Preciado and Alejandro Ribeiro. “A Prediction-Correction Primal-Dual Algorithm for Distributed Optimization”. In Proc. American Control Conference, vol. 835-841. Philadelphia, PA, July 10-12 2019.

  35. Maria Peifer, Luiz F.O. Chamon, Santiago Paternain and Alejandro Ribeiro. “Sparse Learning of Parsimonious Reproducing Kernel Hilbert Space Models”. In Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, p.3292-3296. Brighton, UK, May 12-17 2019.

  36. Santiago Paternain , Juan Andrés Bazerque, Austin Small and Alejandro Ribeiro. “Learning Policies for Markov Decision Processes in Continuous Spaces”. In Proc. IEEE 57th Annual Conference on Decision and Control (CDC), vol. 4751-4758. Miami, FL, December 17-19 2018.

  37. Santiago Paternain , Aryan Mokthari and Alejandro Ribeiro. “A Newton Method for Faster Navigation in Cluttered Environments”. In Proc. IEEE 57th Annual Conference on Decision and Control (CDC), vol. 4084-4090. Miami, FL, December 17-19 2018.

  38. Alec Koppel, Santiago Paternain, Cedric Richard and Alejandro Ribeiro. “Decentralized Online Nonparametric Learning”, In Proc. IEEE Asilomar Conference on Signals, Systems and Computers, vol. 2139-2143. Paciffic Grove, CA, October 28-31 2018. (Invited Session)

  39. Maria Peifer, Luiz F.O. Chamon, Santiago Paternain and Alejandro Ribeiro. “Locally Adaptive Kernel Estimation Using Sparse Functional Programming”, In Proc. IEEE Asilomar Conference on Signals, Systems and Computers, vol. 2022-2026. Paciffic Grove, CA, October 28-31 2018.

  40. Santiago Paternain , Manfred Morari and Alejandro Ribeiro. “A Prediction-Correction Method for Model Predictive Control”, In Proc. American Control Conference, vol. 4189-4194. Milwaukee, WI, June 27-29 2018.

  41. Mahyar Fazlyab, Santiago Paternain, Alejandro Ribeiro and Victor M. Preciado. “Distributed Smooth and Strongly Convex Optimization with Inexact Dual Methods”, In Proc. American Control Conference, vol. 3768-3773 Milwaukee, WI, June 27-29 2018.

  42. Santiago Paternain and Alejandro Ribeiro “Safe Online Navigation of Convex Potentials in Spaces with Convex Obstacles”, In proc. 56th Annual Conference on Decision and Control, vol.2473- 2478. Melbourne, Australia. December 12-16 2017. (Best Student Paper Award).

  43. Alec Koppel, Santiago Paternain, Cedric Richard and Alejandro Ribeiro. “Decentralized Efficient Nonparametric Stochastic Optimization”. In Proc. 5th IEEE Global Conference on Signal and Information Processing , vol: 533-537. Montreal, Canada, November 14-16 2017.

  44. Santiago Paternain, Matías Tailanián, Rodrigo Rosa and Rafael Canetti. “Design and Implementation of Flight Control for an Autonomous Quadrotor”, In Proc. 2017 IEEE URUCON , vol.1-4. Montevideo, Uruguay, 23-25 October 2017.

  45. Mahyar Fazlyab, Santiago Paternain, Victor M. Preciado and Alejandro Ribeiro. “Interior Point Method for Dynamic Constrained Optimization in Continuous Time”, In Proc. American Control Conference, vol. 5612-5618. Boston, July 6-8 2015.

  46. Santiago Paternain and Alejandro Ribeiro. “Online Learning of Optimal Strategies in Unknown Environments”, In Proc. 54th Annual Conference on Decision and Control , vol. 3951-3958. Osaka, Japan. December 15-18 2015.

  47. Santiago Paternain and Alejandro Ribeiro. “Online Learning of Feasible Strategies in Unknown Environments”. In Proc. American Control Conference , vol. 4231-4238, Chicago, United States. July 1-3 2015.

  48. Matías Tailanián, Santiago Paternain, Rodrigo Rosa and Rafael Canetti. “Design and Implementation of Sensor Data Fusion for an Autonomous Quadrotor”, In Proc Instrumentation and Measurement Technology Conference (I2MTC) , vol. 1431-1436. Montevideo, Uruguay May 12-15 2014 (Best Student Paper Award).

  49. Santiago Paternain , Matías Tailanián and Rafael Canetti. “Calibration of an Inertial Measurement Unit”, In Proc International Conference on Advanced Robotics (ICAR) , vol. 1-6. Montevideo, Uruguay November 25-29 2013.