Combination of adaptive filters for relative navigation. - Luiz F. O. Chamon; Cássio Guimarães Lopes (EUSIPCO, 2011)

A data reusage algorithm based on incremental combination of LMS filters. - Luiz F. O. Chamon; Humberto F. Ferro; Cássio Guimarães Lopes (ACSCC, 2012)

Combination of adaptive filters with coefficients feedback. - Luiz F. O. Chamon; Wilder Bezerra Lopes; Cássio Guimarães Lopes (ICASSP, 2012)

Transient performance of an incremental combination of LMS filters. - Luiz F. O. Chamon; Cássio Guimarães Lopes (EUSIPCO, 2013)

Towards spatially universal adaptive diffusion networks. - Cássio Guimarães Lopes; Luiz F. O. Chamon; Vítor H. Nascimento (GlobalSIP, 2014)

There's plenty of room at the bottom: Incremental combinations of sign-error LMS filters. - Luiz F. O. Chamon; Cássio Guimarães Lopes (ICASSP, 2014)

Near-optimality of greedy set selection in the sampling of graph signals. - Luiz F. O. Chamon; Alejandro Ribeiro (GlobalSIP, 2016)

Combinations of Adaptive Filters with Coefficients Feedback. - Luiz F. O. Chamon; Cássio Guimarães Lopes (CoRR, 2016)

The mean square error in Kalman filtering sensor selection is approximately supermodular. - Luiz F. O. Chamon; George J. Pappas; Alejandro Ribeiro (CDC, 2017)

Finite-precision effects on graph filters. - Luiz F. O. Chamon; Alejandro Ribeiro (GlobalSIP, 2017)

Universal bounds for the sampling of graph signals. - Luiz F. O. Chamon; Alejandro Ribeiro (ICASSP, 2017)

Approximate Supermodularity Bounds for Experimental Design. - Luiz F. O. Chamon; Alejandro Ribeiro (NIPS, 2017)

Closing the Network Diagnostics Gap with Vigil. - Behnaz Arzani; Selim Ciraci; Luiz F. O. Chamon; Yibo Zhu; Hongqiang Harry Liu; Jitu Padhye; Geoff Outhred; Boon Thau Loo (SIGCOMM Posters and Demos, 2017)

Online Deep Learning in Wireless Communication Systems. - Mark Eisen; Clark Zhang; Luiz F. O. Chamon; Daniel D. Lee; Alejandro Ribeiro (ACSSC, 2018)

Locally Adaptive Kernel Estimation Using Sparse Functional Programming. - Maria Peifer; Luiz F. O. Chamon; Santiago Paternain; Alejandro Ribeiro (ACSSC, 2018)

Strong Duality of Sparse Functional Optimization. - Luiz F. O. Chamon; Yonina C. Eldar; Alejandro Ribeiro (ICASSP, 2018)

007: Democratically Finding the Cause of Packet Drops. - Behnaz Arzani; Selim Ciraci; Luiz F. O. Chamon; Yibo Zhu; Hongqiang Liu; Jitu Padhye; Boon Thau Loo; Geoff Outhred (NSDI, 2018)

Greedy Sampling of Graph Signals. - Luiz F. O. Chamon; Alejandro Ribeiro (IEEE Trans. Signal Process., 2018)

Learning Gaussian Processes with Bayesian Posterior Optimization. - Luiz F. O. Chamon; Santiago Paternain; Alejandro Ribeiro (ACSSC, 2019)

Model Predictive Selection: A Receding Horizon Scheme for Actuator Selection. - Vinícius Lima Silva; Luiz F. O. Chamon; Alejandro Ribeiro (ACC, 2019)

Matroid-Constrained Approximately Supermodular Optimization for Near-Optimal Actuator Scheduling. - Luiz F. O. Chamon; Alexandre Amice; Alejandro Ribeiro (CDC, 2019)

Learning Safe Policies via Primal-Dual Methods. - Santiago Paternain; Miguel Calvo-Fullana; Luiz F. O. Chamon; Alejandro Ribeiro (CDC, 2019)

Sparse Recovery over Nonlinear Dictionaries. - Luiz F. O. Chamon; Yonina C. Eldar; Alejandro Ribeiro (ICASSP, 2019)

Dual Domain Learning of Optimal Resource Allocations in Wireless Systems. - Mark Eisen; Clark Zhang; Luiz F. O. Chamon; Daniel D. Lee; Alejandro Ribeiro (ICASSP, 2019)

Sparse Learning of Parsimonious Reproducing Kernel Hilbert Space Models. - Maria Peifer; Luiz F. O. Chamon; Santiago Paternain; Alejandro Ribeiro (ICASSP, 2019)

Constrained Reinforcement Learning Has Zero Duality Gap. - Santiago Paternain; Luiz F. O. Chamon; Miguel Calvo-Fullana; Alejandro Ribeiro (NeurIPS, 2019)

Risk-Aware MMSE Estimation. - Dionysios S. Kalogerias; Luiz F. O. Chamon; George J. Pappas; Alejandro Ribeiro (CoRR, 2019)

Learning Optimal Resource Allocations in Wireless Systems. - Mark Eisen; Clark Zhang; Luiz F. O. Chamon; Daniel D. Lee; Alejandro Ribeiro (IEEE Trans. Signal Process., 2019)

Resilient Control: Compromising to Adapt. - Luiz F. O. Chamon; Alexandre Amice; Santiago Paternain; Alejandro Ribeiro (CDC, 2020)

Risk-Constrained Linear-Quadratic Regulators. - Anastasios Tsiamis; Dionysios S. Kalogerias; Luiz F. O. Chamon; Alejandro Ribeiro; George J. Pappas (CDC, 2020)

Graphon Filters: Signal Processing in Very Large Graphs. - Luana Ruiz; Luiz F. O. Chamon; Alejandro Ribeiro (EUSIPCO, 2020)

The Empirical Duality Gap of Constrained Statistical Learning. - Luiz F. O. Chamon; Santiago Paternain; Miguel Calvo-Fullana; Alejandro Ribeiro (ICASSP, 2020)

Better Safe Than Sorry: Risk-Aware Nonlinear Bayesian Estimation. - Dionysios S. Kalogerias; Luiz F. O. Chamon; George J. Pappas; Alejandro Ribeiro (ICASSP, 2020)

The Graphon Fourier Transform. - Luana Ruiz; Luiz F. O. Chamon; Alejandro Ribeiro (ICASSP, 2020)

Counterfactual Programming for Optimal Control. - Luiz F. O. Chamon; Santiago Paternain; Alejandro Ribeiro (L4DC, 2020)

Probably Approximately Correct Constrained Learning. - Luiz F. O. Chamon; Alejandro Ribeiro (NeurIPS, 2020)

Graphon Neural Networks and the Transferability of Graph Neural Networks. - Luana Ruiz; Luiz F. O. Chamon; Alejandro Ribeiro (NeurIPS, 2020)

Trust but Verify: Assigning Prediction Credibility by Counterfactual Constrained Learning. - Luiz F. O. Chamon; Santiago Paternain; Alejandro Ribeiro (CoRR, 2020)

Functional Nonlinear Sparse Models. - Luiz F. O. Chamon; Yonina C. Eldar; Alejandro Ribeiro (IEEE Trans. Signal Process., 2020)

Sparse Multiresolution Representations With Adaptive Kernels. - Maria Peifer; Luiz F. O. Chamon; Santiago Paternain; Alejandro Ribeiro (IEEE Trans. Signal Process., 2020)

Transferable Graph Neural Networks on Large-Scale Stochastic Graphs. - Luana Ruiz; Luiz F. O. Chamon; Alejandro Ribeiro (ACSCC, 2021)

Source Seeking in Unknown Environments with Convex Obstacles. - Bruno Augusto Angélico; Luiz F. O. Chamon; Santiago Paternain; Alejandro Ribeiro; George J. Pappas (ACC, 2021)

Towards Safe Continuing Task Reinforcement Learning. - Miguel Calvo-Fullana; Luiz F. O. Chamon; Santiago Paternain (ACC, 2021)

Adversarial Robustness with Semi-Infinite Constrained Learning. - Alexander Robey; Luiz F. O. Chamon; George J. Pappas; Hamed Hassani; Alejandro Ribeiro (NeurIPS, 2021)

Approximate Supermodularity of Kalman Filter Sensor Selection. - Luiz F. O. Chamon; George J. Pappas; Alejandro Ribeiro (IEEE Trans. Autom. Control., 2021)

Graphon Signal Processing. - Luana Ruiz; Luiz F. O. Chamon; Alejandro Ribeiro (IEEE Trans. Signal Process., 2021)

Probabilistically Robust Learning: Balancing Average and Worst-case Performance. - Alexander Robey; Luiz F. O. Chamon; George J. Pappas; Hamed Hassani (ICML, 2022)

Approximately Supermodular Scheduling Subject to Matroid Constraints. - Luiz F. O. Chamon; Alexandre Amice; Alejandro Ribeiro (IEEE Trans. Autom. Control., 2022)

Learning Globally Smooth Functions on Manifolds. - Juan Cerviño; Luiz F. O. Chamon; Benjamin David Haeffele; René Vidal; Alejandro Ribeiro (ICML, 2023)

Automatic Data Augmentation via Invariance-Constrained Learning. - Ignacio Hounie; Luiz F. O. Chamon; Alejandro Ribeiro (ICML, 2023)

Resilient Constrained Learning. - Ignacio Hounie; Alejandro Ribeiro; Luiz F. O. Chamon (NeurIPS, 2023)

Distributed Universal Adaptive Networks. - Cássio Guimarães Lopes; Vítor Heloiz Nascimento; Luiz F. O. Chamon (IEEE Trans. Signal Process., 2023)

Transferability Properties of Graph Neural Networks. - Luana Ruiz; Luiz F. O. Chamon; Alejandro Ribeiro (IEEE Trans. Signal Process., 2023)

Safe Policies for Reinforcement Learning via Primal-Dual Methods. - Santiago Paternain; Miguel Calvo-Fullana; Luiz F. O. Chamon; Alejandro Ribeiro (IEEE Trans. Autom. Control., 2023)

Constrained Learning With Non-Convex Losses. - Luiz F. O. Chamon; Santiago Paternain; Miguel Calvo-Fullana; Alejandro Ribeiro (IEEE Trans. Inf. Theory, 2023)

Near-Optimal Solutions of Constrained Learning Problems. - Juan Elenter; Luiz F. O. Chamon; Alejandro Ribeiro (ICLR, 2024)

Constrained Sampling with Primal-Dual Langevin Monte Carlo. - Luiz F. O. Chamon; Mohammad Reza Karimi Jaghargh; Anna Korba (NeurIPS, 2024)

State Augmented Constrained Reinforcement Learning: Overcoming the Limitations of Learning With Rewards. - Miguel Calvo-Fullana; Santiago Paternain; Luiz F. O. Chamon; Alejandro Ribeiro (IEEE Trans. Autom. Control., 2024)

Solving Differential Equations with Constrained Learning. - Viggo Moro; Luiz F. O. Chamon (ICLR, 2025)

Benign Overfitting and the Geometry of the Ridge Regression Solution in Binary Classification. - Alexander Tsigler; Luiz F. O. Chamon; Spencer Frei; Peter L. Bartlett (CoRR, 2025)

The Lagrangian Method for Solving Constrained Markov Games. - Soham Das 005; Santiago Paternain; Luiz F. O. Chamon; Ceyhun Eksin (CoRR, 2025)

Learning (Approximately) Equivariant Networks via Constrained Optimization. - Andrei Manolache; Luiz F. O. Chamon; Mathias Niepert (CoRR, 2025)