Transforming complex problems into K-means solutions

H Liu, J Chen, J Dy, Y Fu - IEEE transactions on pattern …, 2023‏ - ieeexplore.ieee.org
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 …

Brain-inspired artificial intelligence research: A review

GY Wang, HN Bao, Q Liu, TG Zhou, S Wu… - Science China …, 2024‏ - Springer
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 …

A fast granular-ball-based density peaks clustering algorithm for large-scale data

D Cheng, Y Li, S **a, G Wang… - IEEE Transactions on …, 2023‏ - ieeexplore.ieee.org
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 …

Safe: Synergic data filtering for federated learning in cloud-edge computing

X Xu, H Li, Z Li, X Zhou - IEEE Transactions on Industrial …, 2022‏ - ieeexplore.ieee.org
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 …

Edge-enhanced minimum-margin graph attention network for short text classification

W Ai, Y Wei, H Shao, Y Shou, T Meng, K Li - Expert Systems with …, 2024‏ - Elsevier
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 …

An efficient and adaptive granular-ball generation method in classification problem

S **a, X Dai, G Wang, X Gao… - IEEE Transactions on …, 2022‏ - ieeexplore.ieee.org
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 …

SAR target classification based on integration of ASC parts model and deep learning algorithm

S Feng, K Ji, L Zhang, X Ma… - IEEE Journal of Selected …, 2021‏ - ieeexplore.ieee.org
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 …

K-means clustering with natural density peaks for discovering arbitrary-shaped clusters

D Cheng, J Huang, S Zhang, S **a… - IEEE Transactions on …, 2023‏ - ieeexplore.ieee.org
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 …

Granular ball twin support vector machine with pinball loss function

A Quadir, M Tanveer - IEEE Transactions on Computational …, 2024‏ - ieeexplore.ieee.org
Alzheimer's disease (AD) and Schizophrenia (SCZ) are prominent neurodegenerative
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

J **e, X **ang, S **a, L Jiang… - IEEE Transactions on …, 2024‏ - ieeexplore.ieee.org
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 …