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Luiz F. O. Chamon
Luiz F. O. Chamon
University of Stuttgart
Verified email at simtech.uni-stuttgart.de - Homepage
Title
Cited by
Cited by
Year
Learning optimal resource allocations in wireless systems
M Eisen, C Zhang, LFO Chamon, DD Lee, A Ribeiro
IEEE Transactions on Signal Processing 67 (10), 2775-2790, 2019
2702019
Constrained reinforcement learning has zero duality gap
S Paternain, L Chamon, M Calvo-Fullana, A Ribeiro
Advances in Neural Information Processing Systems 32, 2019
2252019
Graphon neural networks and the transferability of graph neural networks
L Ruiz, L Chamon, A Ribeiro
Advances in Neural Information Processing Systems 33, 1702-1712, 2020
1762020
Greedy sampling of graph signals
LFO Chamon, A Ribeiro
IEEE Transactions on Signal Processing 66 (1), 34-47, 2017
1512017
Safe policies for reinforcement learning via primal-dual methods
S Paternain, M Calvo-Fullana, LFO Chamon, A Ribeiro
IEEE Transactions on Automatic Control 68 (3), 1321-1336, 2022
1352022
007: Democratically finding the cause of packet drops
B Arzani, S Ciraci, L Chamon, Y Zhu, HH Liu, J Padhye, BT Loo, ...
15th USENIX Symposium on Networked Systems Design and Implementation (NSDI …, 2018
1342018
Graphon signal processing
L Ruiz, LFO Chamon, A Ribeiro
IEEE Transactions on Signal Processing 69, 4961-4976, 2021
772021
Probably approximately correct constrained learning
L Chamon, A Ribeiro
Advances in Neural Information Processing Systems 33, 16722-16735, 2020
482020
Adversarial robustness with semi-infinite constrained learning
A Robey, L Chamon, GJ Pappas, H Hassani, A Ribeiro
Advances in Neural Information Processing Systems 34, 6198-6215, 2021
472021
Risk-constrained linear-quadratic regulators
A Tsiamis, DS Kalogerias, LFO Chamon, A Ribeiro, GJ Pappas
2020 59th IEEE Conference on Decision and Control (CDC), 3040-3047, 2020
462020
Transferability properties of graph neural networks
L Ruiz, LFO Chamon, A Ribeiro
IEEE Transactions on Signal Processing 71, 3474-3489, 2023
442023
State augmented constrained reinforcement learning: Overcoming the limitations of learning with rewards
M Calvo-Fullana, S Paternain, LFO Chamon, A Ribeiro
IEEE Transactions on Automatic Control 69 (7), 4275-4290, 2023
412023
Approximate supermodularity bounds for experimental design
L Chamon, A Ribeiro
Advances in Neural Information Processing Systems 30, 2017
412017
Constrained learning with non-convex losses
LFO Chamon, S Paternain, M Calvo-Fullana, A Ribeiro
IEEE Transactions on Information Theory 69 (3), 1739-1760, 2022
402022
The mean square error in Kalman filtering sensor selection is approximately supermodular
LFO Chamon, GJ Pappas, A Ribeiro
2017 IEEE 56th Annual Conference on Decision and Control (CDC), 343-350, 2017
392017
Probabilistically robust learning: Balancing average and worst-case performance
A Robey, L Chamon, GJ Pappas, H Hassani
International Conference on Machine Learning, 18667-18686, 2022
382022
Combination of adaptive filters with coefficients feedback
LFO Chamon, WB Lopes, CG Lopes
IEEE International Conference on Acoustics, Speech and Signal Processing …, 2012
362012
The graphon fourier transform
L Ruiz, LFO Chamon, A Ribeiro
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
342020
Approximate supermodularity of Kalman filter sensor selection
LFO Chamon, GJ Pappas, A Ribeiro
IEEE Transactions on Automatic Control 66 (1), 49-63, 2020
342020
Learning safe policies via primal-dual methods
S Paternain, M Calvo-Fullana, LFO Chamon, A Ribeiro
2019 IEEE 58th Conference on Decision and Control (CDC), 6491-6497, 2019
272019
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