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Probabilistically Robust Learning: Balancing Average- and Worst-case Performance


Feb 02, 2022
Alexander Robey, Luiz F. O. Chamon, George J. Pappas, Hamed Hassani


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Transferability Properties of Graph Neural Networks


Dec 09, 2021
Luana Ruiz, Luiz F. O. Chamon, Alejandro Ribeiro

* Submitted to IEEE TSP 

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Adversarial Robustness with Semi-Infinite Constrained Learning


Oct 29, 2021
Alexander Robey, Luiz F. O. Chamon, George J. Pappas, Hamed Hassani, Alejandro Ribeiro


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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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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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Probably Approximately Correct Constrained Learning


Jun 09, 2020
Luiz F. O. Chamon, Alejandro Ribeiro


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Graphon Neural Networks and the Transferability of Graph Neural Networks


Jun 05, 2020
Luana Ruiz, Luiz F. O. Chamon, 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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