Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
A recent study by two prominent finance researchers, Fama and French, introduces a new framework for studying risk vs. return: the migration of stocks across size-value portfolio ...
Xiaoxi Du, Ruoming Jin, Liang Ding, Victor E. Lee,...
Particle-based simulation methods are used to model a wide range of complex phenomena and to solve time-dependent problems of various scales. Effective visualizations of the resul...
Christiaan P. Gribble, Carson Brownlee, Steven G. ...
Abstract. Traditional stochastic programming is risk neutral in the sense that it is concerned with the optimization of an expectation criterion. A common approach to addressing ri...
Flash memory has become a virtually indispensable component for mobile devices in today’s information society. However, conventional testing methods often fail to detect hidden b...