Finding latent patterns in high dimensional data is an important research problem with numerous applications. The most well known approaches for high dimensional data analysis are...
The problem of selecting the best system from a finite set of alternatives is considered from a Bayesian decision-theoretic perspective. The framework presented is quite general,...
Next-generation scientific applications require the capability to visualize large archival data sets or on-going computer simulations of physical and other phenomena over wide-area...
Qishi Wu, Jinzhu Gao, Mengxia Zhu, Nageswara S. V....
This paper formulates and studies a general continuous-time behavioral portfolio selection model under Kahneman and Tversky's (cumulative) prospect theory, featuring S-shaped...
Naïve Bayes is a well-known effective and efficient classification algorithm, but its probability estimation performance is poor. Averaged One-Dependence Estimators, simply AODE,...