The broad learning system (BLS) has recently been applied in numerous fields. However, it
is mainly a supervised learning system and thus not suitable for specific practical …

Collaborative representation-based classifiers (CRCs) have demonstrated remarkable
classification performance in various pattern recognition fields. However, their success …

Collaborative representation-based classification (CRC) has been extensively applied to
various recognition fields due to its effectiveness and efficiency. Nevertheless, it is generally …

Least squares regression (LSR) has demonstrated promising performance in various
classification tasks owing to its effectiveness and efficiency. However, there are some …

The broad learning system (BLS) has garnered significant attention in the realm of visual
classification due to its exceptional balance between accuracy and efficiency. However, the …

Over-sampling approaches focus on generating samples to balance the dataset and have
been widely applied in classifying imbalanced data. However, existing approaches do not …

Abstract Representation-based methods have found widespread applications in various
classification tasks. However, these methods cannot deal effectively with imbalanced data …

Time/space separation-based methods have been extensively employed in modeling the
lithium-ion battery (LIB) thermal process. However, these methods often adopt linear …

In medical practice, polyp segmentation holds immense significance for early Colorectal
Cancer diagnosis. Over the past decade, techniques based on Deep Learning (DL) have …

Partial multilabel learning (PML) addresses the issue of noisy supervision, which contains
an overcomplete set of candidate labels for each instance with only a valid subset of training …