My name is Luiz Chamon. I study the theoretical underpinnings of constrained learning and its applications in signal processing, control, and machine learning.
April 1st, 2021 – I will be giving an invited seminar at Microsoft Research.
March 23rd, 2021 – "Approximately supermodular scheduling subject to matroid constraints" was accepted for publication on IEEE TAC (arXiv).
March 10th, 2021 – New preprint: "Constrained learning with non-convex losses" (arXiv).
February 26th, 2021 – New papers accepted at ACC 2021:
February 25th, 2021 – New preprint: "State augmented constrained reinforcement learning: Overcoming the limitations of learning with rewards" (arXiv).
February 1st, 2021 – I will be giving an invited seminar at the Massachusetts Institute of Technology (EECS).
January 8th, 2021 – I will be giving an invited seminar at the Johns Hopkins Mathematical Institute for Data Science (MINDS).
January 6th, 2021 – I will be giving an invited seminar at the Toyota Technological Institute at Chicago (TTIC).
December 15th, 2020 – Check out my papers at IEEE CDC this week:
December 5th, 2020 – Check out my papers at NeurIPS next week:
December 3rd, 2020 – I've released the first version of csl, a python package for constrained learning. You can get the package on GitHub and check out applications in fairness and robustness in the documentations.
April 1st, 2020 – New preprint: "Graphon signal processing" submitted to IEEE TSP (arXiv).
March 20th, 2020 – "Functional nonlinear sparse models" was accepted for publication on IEEE TSP (arXiv).
February 7th, 2020 – Patent "Sparse cascaded-integrator-comb filters" with Analog Devices is out.