I'm a fifth year Ph.D. student at Penn working with at Alejandro Ribeiro.
I study the theoretical underpinnings of constrained learning and its applications to signal processing, control, and machine learning.

SELECTED PUBLICATIONS

  • S. Paternain, L.F.O. Chamon, M. Calvo-Fullana, and A. Ribeiro, "Constrained reinforcement learning has zero duality gap."
    NeurIPS 2019.
  • L.F.O. Chamon, Y.C. Eldar, and A. Ribeiro, "Functional nonlinear sparse models." Submitted to IEEE TSP.
  • M. Peifer, L.F.O. Chamon, S. Paternain, and A. Ribeiro, "Sparse multiresolution representations with adaptive kernels."
    Submitted to IEEE TSP.
  • L.F.O. Chamon, A. Ribeiro, and G.J. Pappas, "Approximate supermodularity of Kalman filter sensor selection."
    IEEE TAC (accepted).
  • L.F.O. Chamon and A. Ribeiro, "Greedy sampling of graph signals." IEEE TSP 2018

NEWS

  • February 7th, 2020 — "Approximate supermodularity of Kalman filter sensor selection" was accepted for publication in IEEE TAC (arXiv).
  • February 7th, 2020 — Patent "Sparse cascaded-integrator-comb filters" with Analog Devices is out.
  • January 29th, 2020 — New preprint "Counterfactual Programming for Optimal Control" available on arXiv.