This notebook develops a QPU programming model for an optimization problem that selects a subset and demonstrates it using Ocean software's dwave-hybrid on an example of feature selection for machine ...

Selection is a decision or question. At some point, a program may need to ask a question because it has reached a step where one or more options are available. Depending on the answer given ...

This is the Python project corresponding to my Master Thesis "Stochastic Dyamic Programming applied to Portfolio Selection problem". My report can be found on my ResearchGate profile. This project is ...

Differentiable programming offers us a way to optimize the full chain, including selection cuts that occur during skimming. This contribution investigates applying selection cuts in front of a simple ...

Example 2. In Example 1, each asset is not allowed to ... Zhang, “Quadratic Programming: Algorithms for Nonlinear Programming and Portfolio Selection,” Wuhan University Press, Wuhan, 2006. [8] Z. Z.

Abstract: When learning from high-dimensional data for symbolic regression (SR), genetic programming (GP) typically could not generalize well. Feature selection, as a data preprocessing method, can ...

Abstract: The evolutionary approach of Genetic Programming (GP) has been applied extensively to model various non-linear systems. The distinct advantage of using GP is that prior assumptions for the ...

The course aims to provide a broad knowledge of how to use the programming language R ... data from various health sciences will be used as examples. The course is aimed at those who work, or want to ...