Contrastive learning methods can be applied to deep regression by enforcing label distance
relationships in feature space. However, these methods are limited to labeled data only …

Multi-view learning is a machine learning app0roach aiming to exploit the knowledge
retrieved from data, represented by multiple feature subsets known as views. Co-training is …

In many real-world applications scientists are often confronted with the problem of
incomplete datasets due to several reasons. The direct analysis of datasets with missing …

In real-world machine learning applications, unlabeled training data are readily available,
but labeled data are expensive and hard to obtain. Therefore, semi-supervised learning …

Rock-mechanics parameters such as Young's modulus and Poisson's ratio are critical to
geomechanical analysis and resource exploration. Because these parameters come from …

Operating performance assessment of gold flotation process plays an important role in
improving the metallurgical performances and pursues the best comprehensive economic …

Telemonitoring is the use of electronic devices such as smartphones to remotely monitor
patients. It provides great convenience and enables timely medical decisions. To facilitate …

One of the major aspects affecting the performance of the classification algorithms is the
amount of labeled data which is available during the training phase. It is widely accepted …

Abstracts: Background The utilization of near-infrared (NIR) spectroscopy, in conjunction
with chemometric techniques, has been widely used in a variety of sectors, including …

Nowadays, soft sensor techniques have become promising solutions for enabling real-time
estimation of difficult-to-measure quality variables in industrial processes. However, labeled …