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Santiago Paternain
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2020 – today
- 2024
- [j18]Honglu He, Chen-Lung Lu, Glenn Saunders, John D. Wason, Pinghai Yang, Jeffrey Schoonover, Leo Ajdelsztajn, Santiago Paternain, Agung Julius, John T. Wen:
Fast and Accurate Relative Motion Tracking for Dual Industrial Robots. IEEE Robotics Autom. Lett. 9(11): 10153-10160 (2024) - [j17]Miguel Calvo-Fullana
, Santiago Paternain
State Augmented Constrained Reinforcement Learning: Overcoming the Limitations of Learning With Rewards. IEEE Trans. Autom. Control. 69(7): 4275-4290 (2024) - [j16]Weiqin Chen
Probabilistic Constraint for Safety-Critical Reinforcement Learning. IEEE Trans. Autom. Control. 69(10): 6789-6804 (2024) - [j15]Sergio Rozada
Tensor and Matrix Low-Rank Value-Function Approximation in Reinforcement Learning. IEEE Trans. Signal Process. 72: 1634-1649 (2024) - [c38]Damsara Jayarathne, Santiago Paternain, Sandipan Mishra:
Allocation of Control Authority Between Dynamic Inversion and Reinforcement Learning for Autonomous Helicopter Aerial Refueling. ACC 2024: 2386-2392 - [c37]Jonathan Fried, Santiago Paternain:
Joint Trajectory Optimization for Redundant Manipulators with Constant Path Speed. ACC 2024: 3833-3840 - [c36]Weiqin Chen, James Onyejizu, Long Vu, Lan Hoang, Dharmashankar Subramanian, Koushik Kar, Sandipan Mishra, Santiago Paternain:
Adaptive Primal-Dual Method for Safe Reinforcement Learning. AAMAS 2024: 326-334 - [c35]Han Shen, Santiago Paternain, Gaowen Liu, Ramana Kompella, Tianyi Chen:
A Method for Bilevel Optimization with Convex Lower-Level Problem. ICASSP 2024: 9426-9430 - [c34]Leopoldo Agorio, Sean Van Alen, Miguel Calvo-Fullana, Santiago Paternain, Juan Andrés Bazerque:
Multi-agent assignment via state augmented reinforcement learning. L4DC 2024: 1202-1213 - [c33]Weiqin Chen, Santiago Paternain:
Generalized constraint for probabilistic safe reinforcement learning. L4DC 2024: 1606-1618 - [i27]Anmol Dwivedi, Santiago Paternain, Ali Tajer:
Blackout Mitigation via Physics-guided RL. CoRR abs/2401.09640 (2024) - [i26]Arindam Chowdhury, Santiago Paternain, Gunjan Verma, Ananthram Swami, Santiago Segarra:
Learning Non-myopic Power Allocation in Constrained Scenarios. CoRR abs/2401.10297 (2024) - [i25]Weiqin Chen, James Onyejizu, Long Vu, Lan Hoang, Dharmashankar Subramanian, Koushik Kar, Sandipan Mishra, Santiago Paternain:
Adaptive Primal-Dual Method for Safe Reinforcement Learning. CoRR abs/2402.00355 (2024) - [i24]Honglu He, Chen-Lung Lu, Glenn Saunders, Pinghai Yang, Jeffrey Schoonover, John D. Wason, Santiago Paternain, Agung Julius, John T. Wen:
Fast and Accurate Relative Motion Tracking for Two Industrial Robots. CoRR abs/2404.06687 (2024) - [i23]Leopoldo Agorio, Sean Van Alen, Miguel Calvo-Fullana, Santiago Paternain, Juan Andrés Bazerque:
Multi-agent assignment via state augmented reinforcement learning. CoRR abs/2406.01782 (2024) - [i22]Glory Justin, Santiago Paternain:
Real-Time Small-Signal Security Assessment Using Graph Neural Networks. CoRR abs/2406.02964 (2024) - [i21]Weiqin Chen, Mark S. Squillante, Chai Wah Wu, Santiago Paternain:
A General Control-Theoretic Approach for Reinforcement Learning: Theory and Algorithms. CoRR abs/2406.14753 (2024) - [i20]Weiqin Chen, Sandipan Mishra, Santiago Paternain:
Domain Adaptation for Offline Reinforcement Learning with Limited Samples. CoRR abs/2408.12136 (2024) - [i19]Glory Justin, Santiago Paternain:
Data-driven Under Frequency Load Shedding Using Reinforcement Learning. CoRR abs/2410.04316 (2024) - 2023
- [j14]Santiago Paternain
Safe Policies for Reinforcement Learning via Primal-Dual Methods. IEEE Trans. Autom. Control. 68(3): 1321-1336 (2023) - [j13]Luiz F. O. Chamon
Constrained Learning With Non-Convex Losses. IEEE Trans. Inf. Theory 69(3): 1739-1760 (2023) - [c32]Arindam Chowdhury, Santiago Paternain, Gunjan Verma, Ananthram Swami, Santiago Segarra:
Learning Non-myopic Power Allocation in Constrained Scenarios. ACSSC 2023: 804-808 - [c31]Damsara Jayarathne, Santiago Paternain, Sandipan Mishra:
Safe residual reinforcement learning for helicopter aerial refueling. AIM 2023: 263-269 - [c30]Weiqin Chen, Dharmashankar Subramanian, Santiago Paternain:
Policy Gradients for Probabilistic Constrained Reinforcement Learning. CISS 2023: 1-6 - [i18]Weiqin Chen, Dharmashankar Subramanian, Santiago Paternain:
Probabilistic Constraint for Safety-Critical Reinforcement Learning. CoRR abs/2306.17279 (2023) - 2022
- [j12]Harshat Kumar, Santiago Paternain, Alejandro Ribeiro
Navigation of a quadratic potential with ellipsoidal obstacles. Autom. 146: 110643 (2022) - [j11]Santiago Paternain
Policy Gradient for Continuing Tasks in Discounted Markov Decision Processes. IEEE Trans. Autom. Control. 67(9): 4467-4482 (2022) - [i17]Weiqin Chen, Dharmashankar Subramanian, Santiago Paternain:
Policy Gradients for Probabilistic Constrained Reinforcement Learning. CoRR abs/2210.00596 (2022) - 2021
- [j10]Santiago Paternain
Stochastic Policy Gradient Ascent in Reproducing Kernel Hilbert Spaces. IEEE Trans. Autom. Control. 66(8): 3429-3444 (2021) - [c29]Miguel Calvo-Fullana, Luiz F. O. Chamon, Santiago Paternain:
Towards Safe Continuing Task Reinforcement Learning. ACC 2021: 902-908 - [c28]Bruno Augusto Angélico
Source Seeking in Unknown Environments with Convex Obstacles. ACC 2021: 5055-5061 - [i16]Clark Zhang, Santiago Paternain, Alejandro Ribeiro:
Sufficiently Accurate Model Learning for Planning. CoRR abs/2102.06099 (2021) - [i15]Miguel Calvo-Fullana, Santiago Paternain, Luiz F. O. Chamon, Alejandro Ribeiro:
State Augmented Constrained Reinforcement Learning: Overcoming the Limitations of Learning with Rewards. CoRR abs/2102.11941 (2021) - [i14]Miguel Calvo-Fullana, Luiz F. O. Chamon, Santiago Paternain:
Towards Safe Continuing Task Reinforcement Learning. CoRR abs/2102.12585 (2021) - [i13]Luiz F. O. Chamon, Santiago Paternain, Miguel Calvo-Fullana, Alejandro Ribeiro:
Constrained Learning with Non-Convex Losses. CoRR abs/2103.05134 (2021) - 2020
- [j9]Andrea Simonetto
Time-Varying Convex Optimization: Time-Structured Algorithms and Applications. Proc. IEEE 108(11): 2032-2048 (2020) - [j8]Santiago Paternain
Stochastic Artificial Potentials for Online Safe Navigation. IEEE Trans. Autom. Control. 65(5): 1985-2000 (2020) - [j7]Maria Peifer
Sparse Multiresolution Representations With Adaptive Kernels. IEEE Trans. Signal Process. 68: 2031-2044 (2020) - [j6]Santiago Paternain
Distributed Constrained Online Learning. IEEE Trans. Signal Process. 68: 3486-3499 (2020) - [c27]Harshat Kumar, Santiago Paternain, Alejandro Ribeiro
Navigation of a Quadratic Potential with Star Obstacles. ACC 2020: 2043-2048 - [c26]Luiz F. O. Chamon, Alexandre Amice, Santiago Paternain, Alejandro Ribeiro
Resilient Control: Compromising to Adapt. CDC 2020: 5703-5710 - [c25]Luiz F. O. Chamon, Santiago Paternain, Miguel Calvo-Fullana, Alejandro Ribeiro
The Empirical Duality Gap of Constrained Statistical Learning. ICASSP 2020: 8374-8378 - [c24]Clark Zhang, Arbaaz Khan, Santiago Paternain, Alejandro Ribeiro
Sufficiently Accurate Model Learning. ICRA 2020: 10991-10997 - [c23]Luiz F. O. Chamon, Santiago Paternain, Alejandro Ribeiro:
Counterfactual Programming for Optimal Control. L4DC 2020: 235-244 - [i12]Luiz F. O. Chamon, Santiago Paternain, Miguel Calvo-Fullana, Alejandro Ribeiro:
The empirical duality gap of constrained statistical learning. CoRR abs/2002.05183 (2020) - [i11]Andrea Simonetto, Emiliano Dall'Anese, Santiago Paternain, Geert Leus, Georgios B. Giannakis:
Time-Varying Convex Optimization: Time-Structured Algorithms and Applications. CoRR abs/2006.08500 (2020) - [i10]Santiago Paternain, Juan Andrés Bazerque, Alejandro Ribeiro:
Policy Gradient for Continuing Tasks in Non-stationary Markov Decision Processes. CoRR abs/2010.08443 (2020) - [i9]Luiz F. O. Chamon, Santiago Paternain, Alejandro Ribeiro:
Trust but Verify: Assigning Prediction Credibility by Counterfactual Constrained Learning. CoRR abs/2011.12344 (2020)
2010 – 2019
- 2019
- [j5]Santiago Paternain
A Newton-Based Method for Nonconvex Optimization with Fast Evasion of Saddle Points. SIAM J. Optim. 29(1): 343-368 (2019) - [c22]Luiz F. O. Chamon, Santiago Paternain, Alejandro Ribeiro:
Learning Gaussian Processes with Bayesian Posterior Optimization. ACSSC 2019: 482-486 - [c21]Santiago Paternain, Mahyar Fazlyab
A Prediction-Correction Primal-Dual Algorithm for Distributed Optimization. ACC 2019: 835-841 - [c20]Harshat Kumar, Santiago Paternain, Alejandro Ribeiro:
Navigation of a Quadratic Potential with Ellipsoidal Obstacles. CDC 2019: 4777-4784 - [c19]Santiago Paternain, Manfred Morari, Alejandro Ribeiro:
Real-Time Model Predictive Control Based on Prediction-Correction Algorithms. CDC 2019: 5285-5291 - [c18]Santiago Paternain, Soomin Lee, Michael M. Zavlanos, Alejandro Ribeiro:
Constrained Online Learning in Networks with Sublinear Regret and Fit. CDC 2019: 5486-5493 - [c17]Santiago Paternain, Miguel Calvo-Fullana, Luiz F. O. Chamon, Alejandro Ribeiro:
Learning Safe Policies via Primal-Dual Methods. CDC 2019: 6491-6497 - [c16]Santiago Paternain, Juan Andrés Bazerque
Policy Improvement Directions for Reinforcement Learning in Reproducing Kernel Hilbert Spaces. CDC 2019: 7454-7461 - [c15]Maria Peifer, Luiz F. O. Chamon, Santiago Paternain, Alejandro Ribeiro
Sparse Learning of Parsimonious Reproducing Kernel Hilbert Space Models. ICASSP 2019: 3292-3296 - [c14]Santiago Paternain, Luiz F. O. Chamon, Miguel Calvo-Fullana, Alejandro Ribeiro:
Constrained Reinforcement Learning Has Zero Duality Gap. NeurIPS 2019: 7553-7563 - [i8]Clark Zhang, Arbaaz Khan, Santiago Paternain, Vijay Kumar, Alejandro Ribeiro:
Learning Task Agnostic Sufficiently Accurate Models. CoRR abs/1902.06862 (2019) - [i7]Maria Peifer, Luiz F. O. Chamon, Santiago Paternain, Alejandro Ribeiro:
Sparse multiresolution representations with adaptive kernels. CoRR abs/1905.02797 (2019) - [i6]Bruno Augusto Angélico, Luiz F. O. Chamon, Santiago Paternain, Alejandro Ribeiro, George J. Pappas:
Source Seeking in Unknown Environments with Convex Obstacles. CoRR abs/1909.07496 (2019) - [i5]Santiago Paternain, Luiz F. O. Chamon, Miguel Calvo-Fullana, Alejandro Ribeiro:
Constrained Reinforcement Learning Has Zero Duality Gap. CoRR abs/1910.13393 (2019) - [i4]Santiago Paternain, Miguel Calvo-Fullana, Luiz F. O. Chamon, Alejandro Ribeiro:
Safe Policies for Reinforcement Learning via Primal-Dual Methods. CoRR abs/1911.09101 (2019) - [i3]Santiago Paternain, Manfred Morari, Alejandro Ribeiro:
A Prediction-Correction Algorithm for Real-Time Model Predictive Control. CoRR abs/1911.10051 (2019) - 2018
- [j4]Mahyar Fazlyab
Prediction-Correction Interior-Point Method for Time-Varying Convex Optimization. IEEE Trans. Autom. Control. 63(7): 1973-1986 (2018) - [j3]Santiago Paternain
Navigation Functions for Convex Potentials in a Space With Convex Obstacles. IEEE Trans. Autom. Control. 63(9): 2944-2959 (2018) - [j2]Alec Koppel
Decentralized Online Learning With Kernels. IEEE Trans. Signal Process. 66(12): 3240-3255 (2018) - [c13]Maria Peifer, Luiz F. O. Chamon, Santiago Paternain, Alejandro Ribeiro
Locally Adaptive Kernel Estimation Using Sparse Functional Programming. ACSSC 2018: 2022-2026 - [c12]Alec Koppel, Santiago Paternain, Cédric Richard, Alejandro Ribeiro
Decentralized Online Nonparametric Learning. ACSSC 2018: 2139-2143 - [c11]Mahyar Fazlyab
Distributed Smooth and Strongly Convex Optimization with Inexact Dual Methods. ACC 2018: 3768-3773 - [c10]Santiago Paternain, Manfred Morari, Alejandro Ribeiro
A Prediction-Correction Method for Model Predictive Control. ACC 2018: 4189-4194 - [c9]Santiago Paternain, Aryan Mokhtari, Alejandro Ribeiro
A Newton Method for Faster Navigation in Cluttered Environments. CDC 2018: 4084-4090 - [c8]Santiago Paternain, Juan Andrés Bazerque
Learning Policies for Markov Decision Processes in Continuous Spaces. CDC 2018: 4751-4758 - [i2]Santiago Paternain, Juan Andrés Bazerque, Austin Small, Alejandro Ribeiro:
Stochastic Policy Gradient Ascent in Reproducing Kernel Hilbert Spaces. CoRR abs/1807.11274 (2018) - 2017
- [j1]Santiago Paternain
Online Learning of Feasible Strategies in Unknown Environments. IEEE Trans. Autom. Control. 62(6): 2807-2822 (2017) - [c7]Santiago Paternain, Alejandro Ribeiro
Safe online navigation of convex potentials in spaces with convex obstacles. CDC 2017: 2473-2478 - [c6]Alec Koppel, Santiago Paternain, Cédric Richard, Alejandro Ribeiro
Decentralized efficient nonparametric stochastic optimization. GlobalSIP 2017: 533-537 - [i1]Alec Koppel, Santiago Paternain, Cédric Richard, Alejandro Ribeiro:
Decentralized Online Learning with Kernels. CoRR abs/1710.04062 (2017) - 2016
- [c5]Mahyar Fazlyab
Interior point method for dynamic constrained optimization in continuous time. ACC 2016: 5612-5618 - 2015
- [c4]Santiago Paternain, Alejandro Ribeiro
Online learning of feasible strategies in unknown environments. ACC 2015: 4231-4238 - [c3]Santiago Paternain, Alejandro Ribeiro
Online learning of optimal strategies in unknown environments. CDC 2015: 3951-3958 - 2014
- [c2]Matías Tailanián, Santiago Paternain, Rodrigo Rosa, Rafael M. Canetti:
Design and implementation of sensor data fusion for an autonomous quadrotor. I2MTC 2014: 1431-1436 - 2013
- [c1]Santiago Paternain, Matías Tailanián, Rafael M. Canetti:
Calibration of an inertial measurement unit. ICAR 2013: 1-6
Coauthor Index
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last updated on 2024-11-13 23:46 CET by the dblp team
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