Santiago Paternain

108 papers A* 2A 1C 12Misc 8Journal 63Unranked 22

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Actor-Curator: Co-adaptive Curriculum Learning via Policy-Improvement Bandits for RL Post-Training. CoRR Zhengyao Gu, Jonathan Light, Raul Astudillo, Ziyu Ye, Langzhou He, Henry Peng Zou, Wei Cheng, Santiago Paternain, Philip S. Yu, Yisong Yue
2026	J	`jnl`	Provable Domain Adaptation for Offline Reinforcement Learning with Limited Samples. Trans. Mach. Learn. Res. Weiqin Chen, Xinjie Zhang, Sandipan Mishra, Santiago Paternain
2025	J	`jnl`	A Bi-Level Optimization Method for Redundant Dual-Arm Minimum Time Problems. CoRR Jonathan Fried, Santiago Paternain
2025	J	`jnl`	A Bi-Level Optimization Method for Redundant Dual-Arm Minimum Time Problems. IEEE Control. Syst. Lett. Jonathan Fried, Santiago Paternain
2025	—	`conf`	A Lagrangian Framework for Safe Cooperative Reinforcement Learning. CDC Soham Das, Luiz F. O. Chamon, Santiago Paternain, Ceyhun Eksin
2025	J	`jnl`	A Tensor Low-Rank Approximation for Value Functions in Multi-Task Reinforcement Learning. CoRR Sergio Rozada, Santiago Paternain, Juan Andrés Bazerque, Antonio G. Marques
2025	C	`conf`	Autonomous helicopter aerial refueling: controller design and performance guarantees. ACC Damsara Jayarathne, Santiago Paternain, Sandipan Mishra
2025	J	`jnl`	Autonomous helicopter aerial refueling: controller design and performance guarantees. CoRR Damsara Jayarathne, Santiago Paternain, Sandipan Mishra
2025	—	`conf`	Bilinear Decomposition of Mixed Integer Linear Programs for Multi-Agent Motion Planning on Quantum Computers. CAMSAP Leopoldo Agorio, Santiago Paternain, Juan Andrés Bazerque
2025	J	`jnl`	ConstrainedSQL: Training LLMs for Text2SQL via Constrained Reinforcement Learning. CoRR Weiqin Chen, Nhan Huu Pham, Michael Robert Glass, Long Hai Vu, Gaetano Rossiello, Dharmashankar Subramanian, Santiago Paternain
2025	J	`jnl`	Cooperative Multi-Agent Assignment over Stochastic Graphs via Constrained Reinforcement Learning. CoRR Leopoldo Agorio, Sean Van Alen, Santiago Paternain, Miguel Calvo-Fullana, Juan Andrés Bazerque
2025	J	`jnl`	DISC: Dynamic Decomposition Improves LLM Inference Scaling. CoRR Jonathan Light, Wei Cheng, Yue Wu, Masafumi Oyamada, Mengdi Wang, Santiago Paternain, Haifeng Chen
2025	J	`jnl`	Filtering Learning Histories Enhances In-Context Reinforcement Learning. CoRR Weiqin Chen, Xinjie Zhang, Dharmashankar Subramanian, Santiago Paternain
2025	J	`jnl`	Learning Closed-Loop Parametric Nash Equilibria of Multi-Agent Collaborative Field Coverage. CoRR Jushan Chen, Santiago Paternain
2025	—	`conf`	Multi-Agent Assignment over Stochastic Graphs via Learning Feasibility. CDC Leopoldo Agorio, Sean Van Alen, Santiago Paternain, Miguel Calvo-Fullana, Juan Andrés Bazerque
2025	J	`jnl`	PAD-TRO: Projection-Augmented Diffusion for Direct Trajectory Optimization. CoRR Jushan Chen, Santiago Paternain
2025	J	`jnl`	Random Policy Enables In-Context Reinforcement Learning within Trust Horizons. Trans. Mach. Learn. Res. Weiqin Chen, Santiago Paternain
2025	J	`jnl`	The Lagrangian Method for Solving Constrained Markov Games. CoRR Soham Das, Santiago Paternain, Luiz F. O. Chamon, Ceyhun Eksin
2025	C	`conf`	Transfer Learning for a Class of Cascade Dynamical Systems. ACC Shima Rabiei, Sandipan Mishra, Santiago Paternain
2025	—	`conf`	User Association in Wireless Networks with Distributed GNN-Based Reinforcement Learning. NTMS Martín Randall, Santiago Paternain, Pedro Casas, Federico Larroca, Pablo Belzarena
2024	J	`jnl`	A Bi-Level Optimization Approach to Joint Trajectory Optimization for Redundant Manipulators. CoRR Jonathan Fried, Santiago Paternain
2024	J	`jnl`	A General Control-Theoretic Approach for Reinforcement Learning: Theory and Algorithms. CoRR Weiqin Chen, Mark S. Squillante, Chai Wah Wu, Santiago Paternain
2024	Misc	`conf`	A Method for Bilevel Optimization with Convex Lower-Level Problem. ICASSP Han Shen, Santiago Paternain, Gaowen Liu, Ramana Kompella, Tianyi Chen
2024	—	`conf`	A Tensor Low-Rank Approximation for Value Functions in Multi-Task Reinforcement Learning. IEEECONF Sergio Rozada, Santiago Paternain, Juan Andrés Bazerque, Antonio G. Marques
2024	A	`conf`	Adaptive Primal-Dual Method for Safe Reinforcement Learning. AAMAS Weiqin Chen, James Onyejizu, Long Vu, Lan Hoang, Dharmashankar Subramanian, Koushik Kar, Sandipan Mishra, Santiago Paternain
2024	J	`jnl`	Adaptive Primal-Dual Method for Safe Reinforcement Learning. CoRR Weiqin Chen, James Onyejizu, Long Vu, Lan Hoang, Dharmashankar Subramanian, Koushik Kar, Sandipan Mishra, Santiago Paternain
2024	C	`conf`	Allocation of Control Authority Between Dynamic Inversion and Reinforcement Learning for Autonomous Helicopter Aerial Refueling. ACC Damsara Jayarathne, Santiago Paternain, Sandipan Mishra
2024	J	`jnl`	Blackout Mitigation via Physics-guided RL. CoRR Anmol Dwivedi, Santiago Paternain, Ali Tajer
2024	J	`jnl`	Data-driven Under Frequency Load Shedding Using Reinforcement Learning. CoRR Glory Justin, Santiago Paternain
2024	J	`jnl`	Domain Adaptation for Offline Reinforcement Learning with Limited Samples. CoRR Weiqin Chen, Sandipan Mishra, Santiago Paternain
2024	J	`jnl`	Fast and Accurate Relative Motion Tracking for Dual Industrial Robots. IEEE Robotics Autom. Lett. Honglu He, Chen-Lung Lu, Glenn Saunders, John D. Wason, Pinghai Yang, Jeffrey Schoonover, Leo Ajdelsztajn, Santiago Paternain, Agung Julius, John T. Wen
2024	J	`jnl`	Fast and Accurate Relative Motion Tracking for Two Industrial Robots. CoRR Honglu He, Chen-Lung Lu, Glenn Saunders, Pinghai Yang, Jeffrey Schoonover, John D. Wason, Santiago Paternain, Agung Julius, John T. Wen
2024	—	`conf`	Generalized constraint for probabilistic safe reinforcement learning. L4DC Weiqin Chen, Santiago Paternain
2024	C	`conf`	Joint Trajectory Optimization for Redundant Manipulators with Constant Path Speed. ACC Jonathan Fried, Santiago Paternain
2024	J	`jnl`	Learning Non-myopic Power Allocation in Constrained Scenarios. CoRR Arindam Chowdhury, Santiago Paternain, Gunjan Verma, Ananthram Swami, Santiago Segarra
2024	—	`conf`	Multi-agent assignment via state augmented reinforcement learning. L4DC Leopoldo Agorio, Sean Van Alen, Miguel Calvo-Fullana, Santiago Paternain, Juan Andrés Bazerque
2024	J	`jnl`	Multi-agent assignment via state augmented reinforcement learning. CoRR Leopoldo Agorio, Sean Van Alen, Miguel Calvo-Fullana, Santiago Paternain, Juan Andrés Bazerque
2024	J	`jnl`	Probabilistic Constraint for Safety-Critical Reinforcement Learning. IEEE Trans. Autom. Control. Weiqin Chen, Dharmashankar Subramanian, Santiago Paternain
2024	J	`jnl`	RL for Mitigating Cascading Failures: Targeted Exploration via Sensitivity Factors. CoRR Anmol Dwivedi, Ali Tajer, Santiago Paternain, Nurali Virani
2024	J	`jnl`	Real-Time Small-Signal Security Assessment Using Graph Neural Networks. CoRR Glory Justin, Santiago Paternain
2024	J	`jnl`	SAD: State-Action Distillation for In-Context Reinforcement Learning under Random Policies. CoRR Weiqin Chen, Santiago Paternain
2024	J	`jnl`	State Augmented Constrained Reinforcement Learning: Overcoming the Limitations of Learning With Rewards. IEEE Trans. Autom. Control. Miguel Calvo-Fullana, Santiago Paternain, Luiz F. O. Chamon, Alejandro Ribeiro
2024	J	`jnl`	Tensor and Matrix Low-Rank Value-Function Approximation in Reinforcement Learning. IEEE Trans. Signal Process. Sergio Rozada, Santiago Paternain, Antonio G. Marques
2024	J	`jnl`	Transfer Learning for a Class of Cascade Dynamical Systems. CoRR Shima Rabiei, Sandipan Mishra, Santiago Paternain
2023	J	`jnl`	Constrained Learning With Non-Convex Losses. IEEE Trans. Inf. Theory Luiz F. O. Chamon, Santiago Paternain, Miguel Calvo-Fullana, Alejandro Ribeiro
2023	Misc	`conf`	Learning Non-myopic Power Allocation in Constrained Scenarios. ACSSC Arindam Chowdhury, Santiago Paternain, Gunjan Verma, Ananthram Swami, Santiago Segarra
2023	Misc	`conf`	Policy Gradients for Probabilistic Constrained Reinforcement Learning. CISS Weiqin Chen, Dharmashankar Subramanian, Santiago Paternain
2023	J	`jnl`	Probabilistic Constraint for Safety-Critical Reinforcement Learning. CoRR Weiqin Chen, Dharmashankar Subramanian, Santiago Paternain
2023	J	`jnl`	Safe Policies for Reinforcement Learning via Primal-Dual Methods. IEEE Trans. Autom. Control. Santiago Paternain, Miguel Calvo-Fullana, Luiz F. O. Chamon, Alejandro Ribeiro
2023	—	`conf`	Safe residual reinforcement learning for helicopter aerial refueling. AIM Damsara Jayarathne, Santiago Paternain, Sandipan Mishra
2022	J	`jnl`	Navigation of a quadratic potential with ellipsoidal obstacles. Autom. Harshat Kumar, Santiago Paternain, Alejandro Ribeiro
2022	J	`jnl`	Policy Gradient for Continuing Tasks in Discounted Markov Decision Processes. IEEE Trans. Autom. Control. Santiago Paternain, Juan Andrés Bazerque, Alejandro Ribeiro
2022	J	`jnl`	Policy Gradients for Probabilistic Constrained Reinforcement Learning. CoRR Weiqin Chen, Dharmashankar Subramanian, Santiago Paternain
2021	J	`jnl`	Constrained Learning with Non-Convex Losses. CoRR Luiz F. O. Chamon, Santiago Paternain, Miguel Calvo-Fullana, Alejandro Ribeiro
2021	C	`conf`	Source Seeking in Unknown Environments with Convex Obstacles. ACC Bruno Augusto Angélico, Luiz F. O. Chamon, Santiago Paternain, Alejandro Ribeiro, George J. Pappas
2021	J	`jnl`	State Augmented Constrained Reinforcement Learning: Overcoming the Limitations of Learning with Rewards. CoRR Miguel Calvo-Fullana, Santiago Paternain, Luiz F. O. Chamon, Alejandro Ribeiro
2021	J	`jnl`	Stochastic Policy Gradient Ascent in Reproducing Kernel Hilbert Spaces. IEEE Trans. Autom. Control. Santiago Paternain, Juan Andrés Bazerque, Austin Small, Alejandro Ribeiro
2021	J	`jnl`	Sufficiently Accurate Model Learning for Planning. CoRR Clark Zhang, Santiago Paternain, Alejandro Ribeiro
2021	C	`conf`	Towards Safe Continuing Task Reinforcement Learning. ACC Miguel Calvo-Fullana, Luiz F. O. Chamon, Santiago Paternain
2021	J	`jnl`	Towards Safe Continuing Task Reinforcement Learning. CoRR Miguel Calvo-Fullana, Luiz F. O. Chamon, Santiago Paternain
2020	—	`conf`	Counterfactual Programming for Optimal Control. L4DC Luiz F. O. Chamon, Santiago Paternain, Alejandro Ribeiro
2020	J	`jnl`	Distributed Constrained Online Learning. IEEE Trans. Signal Process. Santiago Paternain, Soomin Lee, Michael M. Zavlanos, Alejandro Ribeiro
2020	C	`conf`	Navigation of a Quadratic Potential with Star Obstacles. ACC Harshat Kumar, Santiago Paternain, Alejandro Ribeiro
2020	J	`jnl`	Policy Gradient for Continuing Tasks in Non-stationary Markov Decision Processes. CoRR Santiago Paternain, Juan Andrés Bazerque, Alejandro Ribeiro
2020	—	`conf`	Resilient Control: Compromising to Adapt. CDC Luiz F. O. Chamon, Alexandre Amice, Santiago Paternain, Alejandro Ribeiro
2020	J	`jnl`	Sparse Multiresolution Representations With Adaptive Kernels. IEEE Trans. Signal Process. Maria Peifer, Luiz F. O. Chamon, Santiago Paternain, Alejandro Ribeiro
2020	J	`jnl`	Stochastic Artificial Potentials for Online Safe Navigation. IEEE Trans. Autom. Control. Santiago Paternain, Alejandro Ribeiro
2020	A*	`conf`	Sufficiently Accurate Model Learning. ICRA Clark Zhang, Arbaaz Khan, Santiago Paternain, Alejandro Ribeiro
2020	Misc	`conf`	The Empirical Duality Gap of Constrained Statistical Learning. ICASSP Luiz F. O. Chamon, Santiago Paternain, Miguel Calvo-Fullana, Alejandro Ribeiro
2020	J	`jnl`	The empirical duality gap of constrained statistical learning. CoRR Luiz F. O. Chamon, Santiago Paternain, Miguel Calvo-Fullana, Alejandro Ribeiro
2020	J	`jnl`	Time-Varying Convex Optimization: Time-Structured Algorithms and Applications. CoRR Andrea Simonetto, Emiliano Dall'Anese, Santiago Paternain, Geert Leus, Georgios B. Giannakis
2020	J	`jnl`	Time-Varying Convex Optimization: Time-Structured Algorithms and Applications. Proc. IEEE Andrea Simonetto, Emiliano Dall'Anese, Santiago Paternain, Geert Leus, Georgios B. Giannakis
2020	J	`jnl`	Trust but Verify: Assigning Prediction Credibility by Counterfactual Constrained Learning. CoRR Luiz F. O. Chamon, Santiago Paternain, Alejandro Ribeiro
2019	J	`jnl`	A Newton-Based Method for Nonconvex Optimization with Fast Evasion of Saddle Points. SIAM J. Optim. Santiago Paternain, Aryan Mokhtari, Alejandro Ribeiro
2019	J	`jnl`	A Prediction-Correction Algorithm for Real-Time Model Predictive Control. CoRR Santiago Paternain, Manfred Morari, Alejandro Ribeiro
2019	C	`conf`	A Prediction-Correction Primal-Dual Algorithm for Distributed Optimization. ACC Santiago Paternain, Mahyar Fazlyab, Victor M. Preciado, Alejandro Ribeiro
2019	—	`conf`	Constrained Online Learning in Networks with Sublinear Regret and Fit. CDC Santiago Paternain, Soomin Lee, Michael M. Zavlanos, Alejandro Ribeiro
2019	A*	`conf`	Constrained Reinforcement Learning Has Zero Duality Gap. NeurIPS Santiago Paternain, Luiz F. O. Chamon, Miguel Calvo-Fullana, Alejandro Ribeiro
2019	J	`jnl`	Constrained Reinforcement Learning Has Zero Duality Gap. CoRR Santiago Paternain, Luiz F. O. Chamon, Miguel Calvo-Fullana, Alejandro Ribeiro
2019	Misc	`conf`	Learning Gaussian Processes with Bayesian Posterior Optimization. ACSSC Luiz F. O. Chamon, Santiago Paternain, Alejandro Ribeiro
2019	—	`conf`	Learning Safe Policies via Primal-Dual Methods. CDC Santiago Paternain, Miguel Calvo-Fullana, Luiz F. O. Chamon, Alejandro Ribeiro
2019	J	`jnl`	Learning Task Agnostic Sufficiently Accurate Models. CoRR Clark Zhang, Arbaaz Khan, Santiago Paternain, Vijay Kumar, Alejandro Ribeiro
2019	—	`conf`	Navigation of a Quadratic Potential with Ellipsoidal Obstacles. CDC Harshat Kumar, Santiago Paternain, Alejandro Ribeiro
2019	—	`conf`	Policy Improvement Directions for Reinforcement Learning in Reproducing Kernel Hilbert Spaces. CDC Santiago Paternain, Juan Andrés Bazerque, Austin Small, Alejandro Ribeiro
2019	—	`conf`	Real-Time Model Predictive Control Based on Prediction-Correction Algorithms. CDC Santiago Paternain, Manfred Morari, Alejandro Ribeiro
2019	J	`jnl`	Safe Policies for Reinforcement Learning via Primal-Dual Methods. CoRR Santiago Paternain, Miguel Calvo-Fullana, Luiz F. O. Chamon, Alejandro Ribeiro
2019	J	`jnl`	Source Seeking in Unknown Environments with Convex Obstacles. CoRR Bruno Augusto Angélico, Luiz F. O. Chamon, Santiago Paternain, Alejandro Ribeiro, George J. Pappas
2019	Misc	`conf`	Sparse Learning of Parsimonious Reproducing Kernel Hilbert Space Models. ICASSP Maria Peifer, Luiz F. O. Chamon, Santiago Paternain, Alejandro Ribeiro
2019	J	`jnl`	Sparse multiresolution representations with adaptive kernels. CoRR Maria Peifer, Luiz F. O. Chamon, Santiago Paternain, Alejandro Ribeiro
2018	—	`conf`	A Newton Method for Faster Navigation in Cluttered Environments. CDC Santiago Paternain, Aryan Mokhtari, Alejandro Ribeiro
2018	C	`conf`	A Prediction-Correction Method for Model Predictive Control. ACC Santiago Paternain, Manfred Morari, Alejandro Ribeiro
2018	J	`jnl`	Decentralized Online Learning With Kernels. IEEE Trans. Signal Process. Alec Koppel, Santiago Paternain, Cédric Richard, Alejandro Ribeiro
2018	Misc	`conf`	Decentralized Online Nonparametric Learning. ACSSC Alec Koppel, Santiago Paternain, Cédric Richard, Alejandro Ribeiro
2018	C	`conf`	Distributed Smooth and Strongly Convex Optimization with Inexact Dual Methods. ACC Mahyar Fazlyab, Santiago Paternain, Alejandro Ribeiro, Victor M. Preciado
2018	—	`conf`	Learning Policies for Markov Decision Processes in Continuous Spaces. CDC Santiago Paternain, Juan Andrés Bazerque, Austin Small, Alejandro Ribeiro
2018	Misc	`conf`	Locally Adaptive Kernel Estimation Using Sparse Functional Programming. ACSSC Maria Peifer, Luiz F. O. Chamon, Santiago Paternain, Alejandro Ribeiro
2018	J	`jnl`	Navigation Functions for Convex Potentials in a Space With Convex Obstacles. IEEE Trans. Autom. Control. Santiago Paternain, Daniel E. Koditschek, Alejandro Ribeiro
2018	J	`jnl`	Prediction-Correction Interior-Point Method for Time-Varying Convex Optimization. IEEE Trans. Autom. Control. Mahyar Fazlyab, Santiago Paternain, Victor M. Preciado, Alejandro Ribeiro
2018	J	`jnl`	Stochastic Policy Gradient Ascent in Reproducing Kernel Hilbert Spaces. CoRR Santiago Paternain, Juan Andrés Bazerque, Austin Small, Alejandro Ribeiro
2017	J	`jnl`	Decentralized Online Learning with Kernels. CoRR Alec Koppel, Santiago Paternain, Cédric Richard, Alejandro Ribeiro
2017	—	`conf`	Decentralized efficient nonparametric stochastic optimization. GlobalSIP Alec Koppel, Santiago Paternain, Cédric Richard, Alejandro Ribeiro
2017	J	`jnl`	Online Learning of Feasible Strategies in Unknown Environments. IEEE Trans. Autom. Control. Santiago Paternain, Alejandro Ribeiro
2017	—	`conf`	Safe online navigation of convex potentials in spaces with convex obstacles. CDC Santiago Paternain, Alejandro Ribeiro
2016	C	`conf`	Interior point method for dynamic constrained optimization in continuous time. ACC Mahyar Fazlyab, Santiago Paternain, Victor M. Preciado, Alejandro Ribeiro
2015	C	`conf`	Online learning of feasible strategies in unknown environments. ACC Santiago Paternain, Alejandro Ribeiro
2015	—	`conf`	Online learning of optimal strategies in unknown environments. CDC Santiago Paternain, Alejandro Ribeiro
2014	—	`conf`	Design and implementation of sensor data fusion for an autonomous quadrotor. I2MTC Matías Tailanián, Santiago Paternain, Rodrigo Rosa, Rafael M. Canetti
2013	—	`conf`	Calibration of an inertial measurement unit. ICAR Santiago Paternain, Matías Tailanián, Rafael M. Canetti