In this article, we present the Group Asymmetric Multi-Task Learning (GAMTL) algorithm that
automatically learns from data how tasks transfer information among themselves at the level …

In order to meet the increasing demand for food safety and quality, new methods for
simultaneous and rapid determination of multiple food quality parameters (FQPs) are …

As an effective learning paradigm against insufficient training samples, multi-task learning
(MTL) encourages knowledge sharing across multiple related tasks so as to improve the …

When the human brain learns multiple related or continuous tasks, it will produce knowledge
sharing and transfer. Thus, fast and effective task learning can be realized. This idea leads …

In multi-task learning (MTL), multiple prediction tasks are learned jointly, such that
generalization performance is improved by transferring information across the tasks …

Modern manufacturing industries are often featured with a data-rich environment. The real-
time behaviors of process variables can be completely recorded as multiple various signal …

Robust group lasso regression plays an important role in high-dimensional regression
modeling such as biological data analysis for disease diagnosis and gene expression …

Quantile regression is one of the most frequently used topics in data analysis. In this article,
we proposed the shrinkage estimator for penalized quantile regression that combines SCAD …

Artificial intelligence and machine learning have become one of the fastest growing and
most popular fields in technology today. Classification algorithms constitute one of the …

ABSTRACT Multi-Task Learning focuses on the simultaneous learning of multiple tasks-
classification or regression tasks, for example-expecting to improve performance on each …