Background and MotivationAccurately pricing American-style options, which allow early exercise at any time before expiry, remains a significant ...

In engineering design, the traditional “deterministic” modelling approach assumes fixed values for loads, material properties ...

ABSTRACT: The development of artificial intelligence (AI), particularly deep learning, has made it possible to accelerate and improve the processing of data collected in different fields (commerce, ...

If the ‘That verification method isn’t working right now‘ message appears due to traffic issues, it should automatically be resolved after a certain period of time. In other cases, use these fixes: ...

Reinforcement learning (RL) is a specialized area of machine learning where agents are trained to make decisions by interacting with their environment. This interaction involves taking action and ...

Abstract: In this work, we investigate stochastic quasi-Newton methods for minimizing a finite sum of cost functions over a decentralized network. We first develop a general algorithmic framework, in ...

The operational uncertainty of the power system is significantly increased by the high penetration of renewable energy and diversification of load behavior, which have aroused the novel research on ...

Abstract: In this article, we propose a full-wave numerical approach called stochastic method of moments (SMoM), for analyzing the effects of uncertainties in the locations of elements in a random ...

I like both chromatography and Marvel movies, and an idea came to me as a result: Why not examine a chromatographic separation process from an Ant-Man perspective? I used the stochastic theory of ...