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Transforming complex problems into K-means solutions
K-means is a fundamental clustering algorithm widely used in both academic and industrial
applications. Its popularity can be attributed to its simplicity and efficiency. Studies show the …
applications. Its popularity can be attributed to its simplicity and efficiency. Studies show the …
Brain-inspired artificial intelligence research: A review
Artificial intelligence (AI) systems surpass certain human intelligence abilities in a statistical
sense as a whole, but are not yet the true realization of these human intelligence abilities …
sense as a whole, but are not yet the true realization of these human intelligence abilities …
A fast granular-ball-based density peaks clustering algorithm for large-scale data
Density peaks clustering algorithm (DP) has difficulty in clustering large-scale data, because
it requires the distance matrix to compute the density and-distance for each object, which …
it requires the distance matrix to compute the density and-distance for each object, which …
Safe: Synergic data filtering for federated learning in cloud-edge computing
With the increasing data scale in the Industrial Internet of Things, edge computing
coordinated with machine learning is regarded as an effective way to raise the novel latency …
coordinated with machine learning is regarded as an effective way to raise the novel latency …
Edge-enhanced minimum-margin graph attention network for short text classification
With the rapid advancement of the internet, there has been a dramatic increase in short-text
data. Due to the brevity of short texts, sparse features, and limited contextual information …
data. Due to the brevity of short texts, sparse features, and limited contextual information …
An efficient and adaptive granular-ball generation method in classification problem
Granular-ball computing (GBC) is an efficient, robust, and scalable learning method for
granular computing. The granular ball (GB) generation method is based on GB computing …
granular computing. The granular ball (GB) generation method is based on GB computing …
SAR target classification based on integration of ASC parts model and deep learning algorithm
Automatic target recognition of synthetic aperture radar (SAR) images has been a vital issue
in recent studies. The recognition methods can be divided into two main types: traditional …
in recent studies. The recognition methods can be divided into two main types: traditional …
K-means clustering with natural density peaks for discovering arbitrary-shaped clusters
Due to simplicity, K-means has become a widely used clustering method. However, its
clustering result is seriously affected by the initial centers and the allocation strategy makes …
clustering result is seriously affected by the initial centers and the allocation strategy makes …
Granular ball twin support vector machine with pinball loss function
Alzheimer's disease (AD) and Schizophrenia (SCZ) are prominent neurodegenerative
conditions and leading causes of dementia, resulting in progressive cognitive decline and …
conditions and leading causes of dementia, resulting in progressive cognitive decline and …
MGNR: A multi-granularity neighbor relationship and its application in KNN classification and clustering methods
In the real world, data distributions often exhibit multiple granularities. However, the majority
of existing neighbor-based machine-learning methods rely on manually setting a single …
of existing neighbor-based machine-learning methods rely on manually setting a single …