no code implementations • 20 Jan 2023 • Julio Guerrero, Maria del Carmen Galiano, Giuseppe Orlando
The main objective of this work is to test whether some stochastic models typically used in financial markets could be applied to the COVID-19 pandemic.
no code implementations • 27 Jan 2022 • Julio Guerrero, Giuseppe Orlando
In this paper, we show that a time-dependent local stochastic volatility (SLV) model can be reduced to a system of autonomous PDEs that can be solved using the Heat kernel, by means of the Wei-Norman factorization method and Lie algebraic techniques.
1 code implementation • 10 Mar 2015 • German Ros, Julio Guerrero
We address the problem of efficient sparse fixed-rank (S-FR) matrix decomposition, i. e., splitting a corrupted matrix $M$ into an uncorrupted matrix $L$ of rank $r$ and a sparse matrix of outliers $S$.
no code implementations • 22 Oct 2014 • German Ros, Jose Alvarez, Julio Guerrero
To this end we propose the Robust Decomposition with Constrained Rank (RD-CR), a proximal gradient based method that enforces the rank constraints inherent to motion estimation.