Abstract: Feature selection is considered as a crucial step in machine learning, particularly when dealing with dimensional dataset. Feature selection involves selecting a subset of the most relevant ...

High-dimensional data often contain noisy and redundant features, posing challenges for accurate and efficient feature selection. To address this, a dynamic multitask learning framework is proposed, ...

This repository contains example controllers and reference implementations for a planar two-joint manipulator. The projects demonstrate different control approaches: adaptive control, robust control, ...

Abstract: The main purpose of feature selection (FS) is to reduce the data dimension and reduce the classification error rate. Therefore, it can be regarded as a ...