Most of the existing anomaly detection methods are based on a single and fine granularity
input pattern, which is susceptible to noisy data and inefficient for detecting anomalies …

Granular-ball support vector machine (GBSVM) is a significant attempt to construct a
classifier using the coarse-to-fine granularity of a granular ball as input, rather than a single …

This paper presents a novel framework for continual feature selection (CFS) in data
preprocessing, particularly in the context of an open and dynamic environment where …

Attribute reduction is a key step in processing large-scale datasets, where the Granular Ball
Neighborhood Rough Set (GBNRS) can significantly enhance the performance of attribute …

The policies learned by humans in simple scenarios can be deployed in complex scenarios
with the same task logic through limited feature alignment training, a process referred to as …