In this paper we introduce XCSF with support vector prediction: the problem of learning the prediction function is solved as a support vector regression problem and each classifie...
The calculation of value-at-risk (VAR) for large portfolios of complex instruments is among the most demanding and widespread computational challenges facing the financial industr...
Paul Glasserman, Philip Heidelberger, Perwez Shaha...
A new framework of compressive sensing (CS), namely statistical compressive sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical dist...
The paper studies the problem of distributed static parameter (vector) estimation in sensor networks with nonlinear observation models and imperfect inter-sensor communication. We...
Support vector machines utilizing the 1-norm, typically set up as linear programs (Mangasarian, 2000; Bradley and Mangasarian, 1998), are formulated here as a completely unconstra...