Search Results - "clustering algorithms"

A General 3D Space-Time-Frequency Non-Stationary Model for 6G Channels by Huang, Ziwei, Cheng, Xiang

“…In this paper, a general three-dimensional (3D) space-time-frequency non-stationary model is proposed for sixth generation (6G) channels. From the proposed…”
Get full text

A Taxonomy of Machine Learning Clustering Algorithms, Challenges, and Future Realms by Pitafi, Shahneela, Anwar, Toni, Sharif, Zubair

“…In the field of data mining, clustering has shown to be an important technique. Numerous clustering methods have been devised and put into practice, and most…”
Get full text

Evolutionary Markov Dynamics for Network Community Detection by Wang, Zhen, Wang, Chunyu, Li, Xianghua, Gao, Chao, Li, Xuelong, Zhu, Junyou

“…Community structure division is a crucial problem in the field of network data analysis. Algorithms based on Markov chains are easy to use and provide…”
Get full text

How much can k-means be improved by using better initialization and repeats? by Fränti, Pasi, Sieranoja, Sami

“…•K-means clustering algorithm can be significantly improved by using a better initialization technique, and by repeating (re-starting) the algorithm.•When the…”
Get full text

Multi-IRS and Multi-UAV-Assisted MEC System for 5G/6G Networks: Efficient Joint Trajectory Optimization and Passive Beamforming Framework by Asim, Muhammad, ELAffendi, Mohammed, El-Latif, Ahmed A. Abd

“…This article presents a multi-intelligent reflecting surface (IRS)- and multi-unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) system for…”
Get full text

Practitioner's Guide to Latent Class Analysis: Methodological Considerations and Common Pitfalls by Sinha, Pratik, Calfee, Carolyn S, Delucchi, Kevin L

“…Latent class analysis is a probabilistic modeling algorithm that allows clustering of data and statistical inference. There has been a recent upsurge in the…”
Get more information

Self-Supervised Self-Organizing Clustering Network: A Novel Unsupervised Representation Learning Method by Li, Shuo, Liu, Fang, Jiao, Licheng, Chen, Puhua, Li, Lingling

“…Deep learning-based clustering methods usually regard feature extraction and feature clustering as two independent steps. In this way, the features of all…”
Get full text

A Fuzzy Clustering Algorithm-Based Dynamic Equivalent Modeling Method for Wind Farm With DFIG by Zou, Jianxiao, Peng, Chao, Xu, Hongbing, Yan, Yan

“…With the increasing capacity of grid connected wind farms, the influence of wind power to stable operation of an electric power system is becoming more and…”
Get full text

An Efficient Framework for Clustered Federated Learning by Ghosh, Avishek, Chung, Jichan, Yin, Dong, Ramchandran, Kannan

“…We address the problem of federated learning (FL) where users are distributed and partitioned into clusters. This setup captures settings where different…”
Get full text

SPICE: Semantic Pseudo-Labeling for Image Clustering by Niu, Chuang, Shan, Hongming, Wang, Ge

“…The similarity among samples and the discrepancy among clusters are two crucial aspects of image clustering. However, current deep clustering methods suffer…”
Get full text

Extended Isolation Forest by Hariri, Sahand, Kind, Matias Carrasco, Brunner, Robert J.

“…We present an extension to the model-free anomaly detection algorithm, Isolation Forest. This extension, named Extended Isolation Forest (EIF), resolves issues…”
Get full text

Fast Markov Clustering Algorithm Based on Belief Dynamics by Li, Huijia, Xu, Wenzhe, Qiu, Chenyang, Pei, Jian

“…Graph clustering is one of the most significant, challenging, and valuable topic in the analysis of real complex networks. To detect the cluster configuration…”
Get full text

Adaptive Asynchronous Clustering Algorithms for Wireless Mesh Networks by Qiao, Cheng, Brown, Kenneth N., Zhang, Fan, Tian, Zhihong

“…It is a challenge to generate an accurate machine learning model in a distributed network due to the increased concern in data privacy and high cost in…”
Get full text

Low-Rank Tensor Graph Learning for Multi-View Subspace Clustering by Chen, Yongyong, Xiao, Xiaolin, Peng, Chong, Lu, Guangming, Zhou, Yicong

“…Graph and subspace clustering methods have become the mainstream of multi-view clustering due to their promising performance. However, (1) since graph…”
Get full text

Placement Optimization of UAV-Mounted Mobile Base Stations by Lyu, Jiangbin, Zeng, Yong, Zhang, Rui, Lim, Teng Joon

“…In terrestrial communication networks without fixed infrastructure, unmanned aerial vehicle-mounted mobile base stations (MBSs) provide an efficient solution…”
Get full text

Fast Parameter-Free Multi-View Subspace Clustering With Consensus Anchor Guidance by Wang, Siwei, Liu, Xinwang, Zhu, Xinzhong, Zhang, Pei, Zhang, Yi, Gao, Feng, Zhu, En

“…Multi-view subspace clustering has attracted intensive attention to effectively fuse multi-view information by exploring appropriate graph structures. Although…”
Get full text

A comprehensive survey of clustering algorithms: State-of-the-art machine learning applications, taxonomy, challenges, and future research prospects by Ezugwu, Absalom E., Ikotun, Abiodun M., Oyelade, Olaide O., Abualigah, Laith, Agushaka, Jeffery O., Eke, Christopher I., Akinyelu, Andronicus A.

“…Clustering is an essential tool in data mining research and applications. It is the subject of active research in many fields of study, such as computer…”
Get full text

Mobility-Aware Cluster Federated Learning in Hierarchical Wireless Networks by Feng, Chenyuan, Yang, Howard H., Hu, Deshun, Zhao, Zhiwei, Quek, Tony Q. S., Min, Geyong

“…Implementing federated learning (FL) algorithms in wireless networks has garnered a wide range of attention. However, few works have considered the impact of…”
Get full text

GMC: Graph-Based Multi-View Clustering by Wang, Hao, Yang, Yan, Liu, Bing

“…Multi-view graph-based clustering aims to provide clustering solutions to multi-view data. However, most existing methods do not give sufficient consideration…”
Get full text

Bootstrap Deep Spectral Clustering with Optimal Transport by Guo, Wengang, Ye, Wei, Chen, Chunchun, Sun, Xin, Bohm, Christian, Plant, Claudia, Rahardja, Susanto

“…Spectral clustering is a leading clustering method. Two of its major shortcomings are the disjoint optimization process and the limited representation…”
Get full text