Suchergebnisse - approximate clustering algorithm

A $(3+\varepsilon)$-Approximate Correlation Clustering Algorithm in Dynamic Streams von Cambus, Mélanie, Kuhn, Fabian, Lindy, Etna, Pai, Shreyas, Uitto, Jara

“… In this paper, we study streaming algorithms for correlation clustering, where each pair of elements is labeled either similar or dissimilar …”
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Fast Density Peaks Clustering Algorithm Based on Approximate k-Nearest Neighbors von Ding, Shifei, Li, Chao, Xu, Xiao, Guo, Lili, Ding, Ling, Wu, Xindong

“… To this end, this paper proposes a fast density peaks clustering algorithm based on approximate k -nearest neighbors (FDPAN …”
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L-ASCRA: A Linearithmic Time Approximate Spectral Clustering Algorithm Using Topologically-Preserved Representatives von Khan, Abdul Atif, Akhter, Mohammad Maksood, Maheshwari, Rashmi, Mohanty, Sraban Kumar

“… Approximate spectral clustering (ASC) algorithms work on the representative points of the data for discovering intrinsic groups …”
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A semi-supervised approximate spectral clustering algorithm based on HMRF model von Ding, Shifei, Jia, Hongjie, Du, Mingjing, Xue, Yu

“… ). This algorithm utilize the mathematical connection between HMRF semi-supervised clustering and approximate weighted kernel k-means …”
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A Novel Approximate Spectral Clustering Algorithm With Dense Cores and Density Peaks von Cheng, Dongdong, Huang, Jinlong, Zhang, Sulan, Zhang, Xiaohua, Luo, Xin

“… This work presents a novel approximate spectral clustering based on dense cores and density peaks, called DCDP-ASC …”
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iMass: an approximate adaptive clustering algorithm for dynamic data using probability based dissimilarity von BHATTACHARJEE, Panthadeep, MITRA, Pinaki

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Approximate k‐Nearest Neighbor Query Algorithm of Two‐Level Index Based on SOM Clustering in High‐Dimensional Space von Zhang, Liping, Hu, Yanming, Li, Sinian, Li, Song, Sun, Guanglu, jin, Haipeng

“… ABSTRACT To address the limitations of traditional high‐dimensional AkNN (Approximate k‐nearest neighbor) query algorithms, which often overlook the data distribution issues, a novel method leveraging SOM …”
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HC_AB: A new heuristic clustering algorithm based on Approximate Backbone von Zong, Yu, Xu, Guandong, Jin, Ping, Zhang, Yanchun, Chen, Enhong

“… Since the clustering problem on numeric data sets can be formulated as a typical combinatorial optimization problem, many researches have addressed the design of heuristic algorithms for finding sub …”
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Behavioral features recognition and oestrus detection based on fast approximate clustering algorithm in dairy cows von Tian, Fuyang, Cao, Dong, Dong, Xiaoning, Zhao, Xinqiang, Li, Fade, Wang, Zhonghua

“… The fast approximate K-means algorithm (FAKM) was proposed to deal the data of the sensor for behavioral features recognition …”
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Exact and approximate algorithms for clustering problem in wireless sensor networks von Yarinezhad, Ramin, Hashemi, Seyed Naser

“… Clustering is an effective method for improving the network lifetime and the overall scalability of a wireless sensor network …”
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A Novel Approximate Spectral Clustering Algorithm With Dense Cores and Density Peaks von Dongdong Cheng, Jinlong Huang, Sulan Zhang, Xiaohua Zhang, Xin Luo

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Fast approximate minimum spanning tree based clustering algorithm von Jothi, R., Mohanty, Sraban Kumar, Ojha, Aparajita

“… •A fast approximate minimum tree based clustering algorithm is proposed.•A novel centroid based nearest neighbor rule is presented …”
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An adaptive flocking algorithm for performing approximate clustering von Folino, Gianluigi, Forestiero, Agostino, Spezzano, Giandomenico

“… This paper presents an approach based on an adaptive bio-inspired method to make state of the art clustering algorithms scalable and to provide them with an any-time behavior …”
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APPROXIMATE ALGORITHMS FOR GRAPH CLUSTERING PROBLEM von Il’ev, V. P., Il’eva, S. D., Morshinin, A. V.

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Fast density clustering strategies based on the k-means algorithm von Bai, Liang, Cheng, Xueqi, Liang, Jiye, Shen, Huawei, Guo, Yike

“… •Propose an accelerated algorithm of density clustering by k-means.•Propose an approximate algorithm of density clustering by k-means …”
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Approximate Clustering Algorithms for High Dimensional Streaming and Distributed Data von Carraher, Lee A

“… ) devices, social network interactions, e-commerce click-streams, scientific monitoring devices, and network traffic, noise robust and distributed clustering algorithms are necessary …”
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A local algorithm to approximate the global clustering of streams generated in ubiquitous sensor networks von Rodrigues, Pedro Pereira, Araújo, João, Gama, João, Lopes, Luís

“… This article presents L2GClust, an algorithm to compute local clusterings at each node as an approximation of the global clustering …”
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Troika algorithm: Approximate optimization for accurate clique partitioning and clustering of weighted networks von Aref, Samin, Ng, Boris

“… Clique partitioning is the fundamental network clustering task of identifying an optimal node partition for a weighted graph according to the real-valued edge weights …”
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Quantum approximate optimization and k-means algorithms for data clustering von Saiphet, Jirawat, Suwanna, Sujin, Chotibut, Thiparat, Chantasri, Areeya

“… Quantum approximate optimization algorithm (QAOA) is a variational hybrid algorithm, which utilizes a NISQ device as a sub-unit for specific tasks and performs most calculations on a classical computer …”
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A distributed approximate nearest neighbors algorithm for efficient large scale mean shift clustering von Beck, Gaël, Duong, Tarn, Lebbah, Mustapha, Azzag, Hanane, Cérin, Christophe

“… We introduce two contributions aiming to provide approximate Mean Shift clustering, based on scalable procedures to compute the density gradient ascent and cluster labeling, with a linear time …”
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