Discover the techniques that help popular scripts succeed.

Abstract: In this paper, two portfolio selection problems including probabilistic future returns with ambiguous expected returns are proposed. Until now, many researchers have proposed models of ...

Roll a die and ask students to identify the random variable. Since a die can only take on values of 1, 2, 3, 4, 5, or 6, this is a discrete random variable. Repeat ...

This tool brute-forces the internal seed of Bash's $RANDOM variable after only 2-3 samples, in seconds. After doing so, you are able to predict all future values to ...

Random forests remain among the most popular off-the-shelf supervised machine learning tools with a well-established track record of predictive accuracy in both regression and classification settings.

Project scheduling problem is mainly to determine the schedule of allocating resources in order to balance the total cost and the completion time. This paper chiefly uses chance theory to introduce ...

ABSTRACT: Many Optimization problems in engineering and economic involve the challenging task of pondering both conflicting goals and random data. In this paper, we give an up-to-date overview of how ...

Abstract: The cold-start problem is a primary factor causing performance loss in collaborative filtering. In this paper, we examine a fatal flaw of existing similarity measures in the cold-start ...