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Constrained Learning with Non-Convex Losses


Mar 08, 2021
Luiz F. O. Chamon, Santiago Paternain, Miguel Calvo-Fullana, Alejandro Ribeiro

* arXiv admin note: text overlap with arXiv:2006.05487 

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Towards Safe Continuing Task Reinforcement Learning


Feb 24, 2021
Miguel Calvo-Fullana, Luiz F. O. Chamon, Santiago Paternain


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State Augmented Constrained Reinforcement Learning: Overcoming the Limitations of Learning with Rewards


Feb 23, 2021
Miguel Calvo-Fullana, Santiago Paternain, Luiz F. O. Chamon, Alejandro Ribeiro


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Sufficiently Accurate Model Learning for Planning


Feb 11, 2021
Clark Zhang, Santiago Paternain, Alejandro Ribeiro


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Trust but Verify: Assigning Prediction Credibility by Counterfactual Constrained Learning


Nov 24, 2020
Luiz F. O. Chamon, Santiago Paternain, Alejandro Ribeiro


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Policy Gradient for Continuing Tasks in Non-stationary Markov Decision Processes


Oct 16, 2020
Santiago Paternain, Juan Andres Bazerque, Alejandro Ribeiro


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The empirical duality gap of constrained statistical learning


Feb 12, 2020
Luiz F. O. Chamon, Santiago Paternain, Miguel Calvo-Fullana, Alejandro Ribeiro


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Safe Policies for Reinforcement Learning via Primal-Dual Methods


Nov 20, 2019
Santiago Paternain, Miguel Calvo-Fullana, Luiz F. O. Chamon, Alejandro Ribeiro

* arXiv admin note: text overlap with arXiv:1910.13393 

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Constrained Reinforcement Learning Has Zero Duality Gap


Oct 29, 2019
Santiago Paternain, Luiz F. O. Chamon, Miguel Calvo-Fullana, Alejandro Ribeiro


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Source Seeking in Unknown Environments with Convex Obstacles


Sep 16, 2019
Bruno A. Angélico, Luiz F. O. Chamon, Santiago Paternain, Alejandro Ribeiro, George J. Pappas

* 8 pages, 13 figures, submitted to ICRA 2020 

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