Matrix computations are ubiquitous in scientific computing and data science. However, many existing methods consume enormous computational resources for solving increasingly large and complex problems. In this talk, I will describe my work on exploiting mathematical structures and hardware capabilities to accelerate matrix computations. I will focus on a randomized algorithm, namely RChol, for computing…

Kornelia Bastin, OR PhD Student People are faced with an overwhelming amount of news, only some of which comes from credible sources and is fact verified. The main idea behind this project is to address such issues. The scope of work includes creating an accessible and efficient method for members of the public to get…

This paper studies the valuation of American options for a general one-factor stochastic volatility model.  Using the local time-space calculus on surfaces we derive an early exercise premium representation for the option price, parametrized by the optimal exercise surface. The exercise surface is the unique solution to an integral equation of Volterra type. The paper…