no code implementations • NeurIPS 2021 • Jose Vinicius de Miranda Cardoso, Jiaxi Ying, Daniel Palomar
Heavy-tailed statistical distributions have long been considered a more realistic statistical model for the data generating process in financial markets in comparison to their Gaussian counterpart.
no code implementations • NeurIPS 2020 • Jiaxi Ying, José Vinícius de Miranda Cardoso , Daniel Palomar
In this paper, we consider the problem of learning a sparse graph from the Laplacian constrained Gaussian graphical model.
2 code implementations • 22 Apr 2019 • Sandeep Kumar, Jiaxi Ying, José Vinícius de M. Cardoso, Daniel Palomar
Then we develop an optimization framework that leverages graph learning with specific structures via spectral constraints on graph matrices.