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0512
Vector based for circular invariant clustering.
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k-means algorithm; Clustering; Genetic algorithms; Optimal partition;
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RBFNN; Co-operative co-evolutionary algorithms; K-means clustering;
Multiclass classification
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K-Means algorithm; K-Means initialization; Voronoi tessellation;
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0804
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Clustering analysis; k-Means; Cluster number; Cost-function; Rival penalized
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Unsupervised classification; Fuzzy clustering; Cluster validity; Fuzzy c-means
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k-Means; Seed selection; Robust initialization; Partitional clustering
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A triangle area based nearest neighbors approach to intrusion detection,
PR(43), No. 1, January 2010, pp. 222-229.
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0909
Intrusion detection; Machine learning; Triangle area; k-means;
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Minimum sum-of-squares clustering; Nonsmooth optimization;
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Segmentation; KPCA; KMeans; Kernel KMeans; GMM; Kernel GMM
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Improvement of the k-means clustering filtering algorithm,
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0810
k-Means clustering; Nearest-neighbor search; Knowledge discovery
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Lai, J.Z.C.[Jim Z.C.],
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k-Means clustering; Nearest-neighbor search; Knowledge discovery
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k nearest neighbors; Fast algorithm; Principal axis search tree;
Orthonormal basis
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1003
Global k-means clustering; Nearest-neighbor search; Knowledge discovery
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Data clustering; Pairwise-nearest-neighbor; Fast search algorithm
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0902
BibRef
And:
Motion segmentation by SCC on the hopkins 155 database,
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IEEE DOI
0910
Linear storage and takes linear running time.
Iterative sampling to improve sampling, reduce outliers.
See also Tensor Decomposition for Geometric Grouping and Segmentation, A.
BibRef
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Wright, J.[John],
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ICCV13(2776-2783)
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1403
Grassmannian Based Hashing; Locality Sensitive Hashing; Subspace Search
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Clustering; Evolutionary computation; Genetic algorithms; K-means
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1002
Clustering; Genetic algorithms; Niching method; Niche migration;
Remote sensing image
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Xiong, H.,
Wu, J.,
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0903
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Hong, Y.,
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0903
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Li, Q.,
Mitianoudis, N.,
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Spatial kernel K-harmonic means clustering for multi-spectral image
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Kashef, R.[Rasha],
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0907
Bisecting clustering; Cooperative clustering; Quality measures
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Kashef, R.[Rasha],
Kamel, M.S.[Mohamed S.],
Cooperative clustering,
PR(43), No. 6, June 2010, pp. 2315-2329.
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1003
Cooperative clustering; Similarity histogram; Cooperative contingency graph
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Chitta, R.[Radha],
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1001
Clustering; k-Means; Classification; Linear-time complexity; Support
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Bagirov, A.M.[Adil M.],
Ugon, J.[Julien],
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1101
Minimum sum-of-squares clustering; Nonsmooth optimization; k-means
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Bagirov, A.M.[Adil M.],
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1602
Cluster analysis
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Karmitsa, N.[Napsu],
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PR(83), 2018, pp. 245-259.
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1808
Cluster analysis, Nonsmooth optimization,
Nonconvex optimization, Bundle methods, Limited memory methods
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Karmitsa, N.[Napsu],
Eronen, V.P.[Ville-Pekka],
Mäkelä, M.M.[Marko M.],
Pahikkala, T.[Tapio],
Airola, A.[Antti],
Stochastic limited memory bundle algorithm for clustering in big data,
PR(165), 2025, pp. 111654.
Elsevier DOI
2505
Clustering, Nonsmooth optimization, Nonconvex optimization,
Stochastic gradient, Limited memory bundle method
BibRef
Erisoglu, M.[Murat],
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Elsevier DOI
1110
k-Means algorithm; Initial cluster centers; Rand index; Error
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BibRef
de Amorim, R.C.[Renato Cordeiro],
Mirkin, B.[Boris],
Minkowski metric, feature weighting and anomalous cluster initializing
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PR(45), No. 3, March 2012, pp. 1061-1075.
Elsevier DOI
1111
K-means; Minkowski metric; Feature weights; Noise features; Anomalous cluster
BibRef
de Amorim, R.C.[Renato Cordeiro],
Shestakov, A.[Andrei],
Mirkin, B.[Boris],
Makarenkov, V.[Vladimir],
The Minkowski central partition as a pointer to a suitable distance
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Elsevier DOI
1704
Clustering
BibRef
Yu, S.[Shi],
Tranchevent, L.[Leon],
Liu, X.H.[Xin-Hai],
Glanzel, W.[Wolfgang],
Suykens, J.A.K.[Johan A.K.],
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PAMI(34), No. 5, May 2012, pp. 1031-1039.
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1204
Combine multiple data sources for k-means.
Code, Clustering. Code:
HTML Version.
BibRef
Liu, F.H.[Fang-Hui],
Huang, X.L.[Xiao-Lin],
Chen, Y.D.[Yu-Dong],
Suykens, J.A.K.[Johan A. K.],
Random Features for Kernel Approximation:
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PAMI(44), No. 10, October 2022, pp. 7128-7148.
IEEE DOI
2209
Kernel, Approximation algorithms, Taxonomy, Scalability,
Risk management, Prediction algorithms, Loss measurement,
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BibRef
Cleuziou, G.[Guillaume],
Osom: A method for building overlapping topological maps,
PRL(34), No. 3, 1 February 2013, pp. 239-246.
Elsevier DOI
1301
BibRef
Earlier:
An extended version of the k-means method for overlapping clustering,
ICPR08(1-4).
IEEE DOI
0812
Unsupervised Learning; Overlapping clustering; Topological maps; Okm;
Som; Osom
BibRef
Sarma, T.H.[T. Hitendra],
Viswanath, P.,
Reddy, B.E.[B. Eswara],
Speeding-up the kernel k-means clustering method: A prototype based
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PRL(34), No. 5, 1 April 2013, pp. 564-573.
Elsevier DOI
1303
BibRef
Earlier: A1, A2, Only:
Speeding-Up the K-Means Clustering Method: A Prototype Based Approach,
PReMI09(56-61).
Springer DOI
0912
Unsupervised classification; Kernel k-means clustering method; Leaders
clustering method
BibRef
Fang, C.L.[Chong-Lun],
Jin, W.[Wei],
Ma, J.W.[Jin-Wen],
K'-Means algorithms for clustering analysis with frequency sensitive
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PRL(34), No. 5, 1 April 2013, pp. 580-586.
Elsevier DOI
1303
Clustering analysis; k-Means; Cluster number; Competitive learning;
Discrepancy metric
BibRef
Tzortzis, G.[Grigorios],
Likas, A.[Aristidis],
The MinMax k-Means clustering algorithm,
PR(47), No. 7, 2014, pp. 2505-2516.
Elsevier DOI
1404
Clustering
BibRef
Malinen, M.I.[Mikko I.],
Mariescu-Istodor, R.[Radu],
Fränti, P.[Pasi],
K-means: Clustering by gradual data transformation,
PR(47), No. 10, 2014, pp. 3376-3386.
Elsevier DOI
1406
BibRef
Earlier:
ICIG11(350-355).
IEEE DOI
1109
Or: K-means*?
Clustering.
BibRef
Malinen, M.I.[Mikko I.],
Fränti, P.[Pasi],
Balanced K-Means for Clustering,
SSSPR14(32-41).
Springer DOI
1408
BibRef
Xu, Q.[Qin],
Ding, C.[Chris],
Liu, J.P.[Jin-Pei],
Luo, B.[Bin],
PCA-guided search for K-means,
PRL(54), No. 1, 2015, pp. 50-55.
Elsevier DOI
1502
K-means
BibRef
Tsapanos, N.[Nikolaos],
Tefas, A.[Anastasios],
Nikolaidis, N.[Nikolaos],
Pitas, I.[Ioannis],
A distributed framework for trimmed Kernel k-Means clustering,
PR(48), No. 8, 2015, pp. 2685-2698.
Elsevier DOI
1505
BibRef
And:
Kernel matrix trimming for improved Kernel K-means clustering,
ICIP15(2285-2289)
IEEE DOI
1512
Data clustering
See also Motivating class-specific nonlinear projections for single and multiple view face verification.
BibRef
Soheily-Khah, S.[Saeid],
Douzal-Chouakria, A.[Ahlame],
Gaussier, E.[Eric],
Generalized k-means-based clustering for temporal data under weighted
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PRL(75), No. 1, 2016, pp. 63-69.
Elsevier DOI
1604
Temporal data
BibRef
Shantaiya, S.[Sanjivani],
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Multiple object clustering using FCM and K-means algorithms,
IJCVR(6), No. 4, 2016, pp. 331-343.
DOI Link
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Rodrigues, É.O.[Érick Oliveira],
Torok, L.[Leonardo],
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Viterbo, J.[José],
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k-MS: A novel clustering algorithm based on morphological
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PR(66), No. 1, 2017, pp. 392-403.
Elsevier DOI
1704
K-Means
BibRef
Li, Z.Q.[Zhen-Qiang],
Guan, X.F.[Xue-Feng],
Wu, H.Y.[Hua-Yi],
Gong, J.Y.[Jian-Ya],
A Novel k-Means Clustering Based Task Decomposition Method for
Distributed Vector-Based CA Models,
IJGI(6), No. 4, 2017, pp. xx-yy.
DOI Link
1705
BibRef
Xu, J.,
Han, J.,
Nie, F.,
Li, X.,
Re-Weighted Discriminatively Embedded K-Means for Multi-View
Clustering,
IP(26), No. 6, June 2017, pp. 3016-3027.
IEEE DOI
1705
Algorithm design and analysis, Clustering algorithms,
Feature extraction, Iterative methods, Linear programming,
Optimization, Robustness, Multi-view clustering,
discriminatively embedded k-means,
iterative re-weighted least squares, low-dimensional, subspace
BibRef
Bai, L.[Liang],
Cheng, X.Q.[Xue-Qi],
Liang, J.[Jiye],
Shen, H.[Huawei],
Guo, Y.[Yike],
Fast density clustering strategies based on the k-means algorithm,
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Elsevier DOI
1707
Cluster, analysis
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Solution improving, Accurate k-means, Iterative improvement
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Evolving clustering, Data stream, Concept drift,
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computational complexity, data compression, image coding,
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1808
feature extraction, image classification,
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1809
Structured sparse clustering, -means clustering,
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Tweet clustering, Scalable K-means, Inverted index
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Data clustering, Inter-center distance,
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1906
Clustering algorithms, K-means, Initialization,
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1909
k-means, Gaussian mixture models, Expectation maximization,
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Yu, H.[Hao],
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Deep clustering, k-Means, Deep learning, Clustering
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clustering, Bipartite graph, Perfect matching, algorithm, Stability
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2101
Semi-supervised clustering, sparse clustering, feature selection
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2103
Global optimization, Clustering, Minimum sum-of-squares,
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Deep Clustering:
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IEEE DOI
2106
Mutual information, Standards, Entropy, Neural networks,
Context modeling, Data models, Analytical models, Deep clustering,
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Huang, S.D.[Shu-Dong],
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PR(117), 2021, pp. 107996.
Elsevier DOI
2106
-means algorithm, Robust clustering, Deep learning
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Xia, S.Y.[Shu-Yin],
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Wei, W.[Wei],
Chen, Z.Z.[Zi-Zhong],
Ball k-Means: Fast Adaptive Clustering With No Bounds,
PAMI(44), No. 1, January 2022, pp. 87-99.
IEEE DOI
2112
Clustering algorithms, Approximation algorithms, Acceleration,
Partitioning algorithms, Standards, Laboratories, Time complexity,
neighbor cluster
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Nie, F.P.[Fei-Ping],
Xue, J.J.[Jing-Jing],
Wu, D.Y.[Dan-Yang],
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Coordinate Descent Method for k-means,
PAMI(44), No. 5, May 2022, pp. 2371-2385.
IEEE DOI
2204
Clustering algorithms, Optimization, Minimization,
Heuristic algorithms, Time complexity, Sparse matrices, Lloyd heuristic
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Wang, R.[Rong],
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Lu, Y.H.[Yi-Hang],
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Discrete and Parameter-Free Multiple Kernel k-Means,
IP(31), No. 2022, pp. 2796-2808.
IEEE DOI
2204
Kernel, Clustering algorithms, Optimization, Correlation,
Analytical models, Redundancy, Matrices, Kernel method,
coordinate descent
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Dorabiala, O.[Olga],
Kutz, J.N.[J. Nathan],
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Robust Trimmed K-Means,
PRL(161), 2022, pp. 9-16.
Elsevier DOI
2209
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Lin, Y.X.[Yun-Xia],
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Rectified Euler k-means and beyond,
PR(137), 2023, pp. 109283.
Elsevier DOI
2302
Kernel -means, Euler kernel, Pseudo centroid, Rectified euler -means
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Mussabayev, R.[Rustam],
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Jarboui, B.[Bassem],
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How to Use K-means for Big Data Clustering?,
PR(137), 2023, pp. 109269.
Elsevier DOI
2302
Big data, Clustering, Minimum sum-of-squares,
Divide and conquer algorithm, Decomposition, K-means, Unsupervised learning
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Laber, E.[Eduardo],
Murtinho, L.[Lucas],
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Shallow decision trees for explainable k-means clustering,
PR(137), 2023, pp. 109239.
Elsevier DOI
2302
Clustering, Explainability, K-means, Decision trees
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Liu, X.W.[Xin-Wang],
SimpleMKKM: Simple Multiple Kernel K-Means,
PAMI(45), No. 4, April 2023, pp. 5174-5186.
IEEE DOI
2303
Kernel, Optimization, Clustering algorithms, Minimization,
Partitioning algorithms, Linear programming, Task analysis,
kernel alignment maximization
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Hu, H.[Haize],
Liu, J.X.[Jian-Xun],
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An Effective and Adaptable K-means Algorithm for Big Data Cluster
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PR(139), 2023, pp. 109404.
Elsevier DOI
2304
-means algorithm, Local optimization, Lévy flight,
Global search, Clustering centroids
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Rezaei, M.[Mohammad],
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K-sets and k-swaps algorithms for clustering sets,
PR(139), 2023, pp. 109454.
Elsevier DOI
2304
Wrapper to prevent local minima.
Clustering sets, Similarity of sets, -means, -medoids,
Random swap, K-swaps, Customer segmentation, Clustering healthcare records
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Liu, H.F.[Hong-Fu],
Chen, J.X.[Jun-Xiang],
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Fu, Y.[Yun],
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PAMI(45), No. 7, July 2023, pp. 9149-9168.
IEEE DOI
2306
Clustering algorithms, Linear programming, Standards,
Iterative methods, Anomaly detection, Euclidean distance,
outlier detection
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Xin, H.[Haonan],
Lu, Y.H.[Yi-Hang],
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Self-Weighted Euler k-Means Clustering,
SPLetters(30), 2023, pp. 1127-1131.
IEEE DOI
2310
BibRef
Guan, X.[Xin],
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Sparse kernel k-means for high-dimensional data,
PR(144), 2023, pp. 109873.
Elsevier DOI
2310
Clustering, Feature selection, Kernel method
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Ping, Y.[Yuan],
Li, H.[Huina],
Hao, B.[Bin],
Guo, C.[Chun],
Wang, B.[Baocang],
Beyond k-Means++: Towards better cluster exploration with geometrical
information,
PR(146), 2024, pp. 110036.
Elsevier DOI
2311
Cluster analysis, k-means++, Support vector data description,
Edge pattern, Division and aggregation
BibRef
He, L.[Li],
Zhang, H.[Hong],
Doubly Stochastic Distance Clustering,
CirSysVideo(33), No. 11, November 2023, pp. 6721-6732.
IEEE DOI
2311
BibRef
Lu, H.[Han],
Xu, H.[Huafu],
Wang, Q.Q.[Qian-Qian],
Gao, Q.X.[Quan-Xue],
Yang, M.[Ming],
Gao, X.B.[Xin-Bo],
Efficient Multi-View K-Means for Image Clustering,
IP(33), 2024, pp. 273-284.
IEEE DOI
2401
BibRef
Han, S.[Soohee],
Lee, J.[Jeongho],
Parallelized Inter-Image k-Means Clustering Algorithm for
Unsupervised Classification of Series of Satellite Images,
RS(16), No. 1, 2024, pp. xx-yy.
DOI Link
2401
BibRef
Shi, K.[Kegong],
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Yang, J.[Jinquan],
A Semantic Partition Algorithm Based on Improved K-Means Clustering
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IJGI(13), No. 2, 2024, pp. 41.
DOI Link
2402
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Pal, S.S.[Shankho Subhra],
Mukhopadhyay, J.[Jayanta],
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Finding hierarchy of clusters,
PRL(178), 2024, pp. 7-13.
Elsevier DOI
2402
Clustering, Hierarchical clustering, Hierarchical relationship,
k-means, Cluster Number Assisted k-Means (CNAK)
BibRef
Su, R.[Rina],
Guo, Y.[Yu],
Wu, C.[Caiying],
Jin, Q.Y.[Qi-Yu],
Zeng, T.Y.[Tie-Yong],
Kernel correlation-dissimilarity for Multiple Kernel k-Means
clustering,
PR(150), 2024, pp. 110307.
Elsevier DOI
2403
k-means, Multiple kernel learning, Consistency,
Frobenius inner product, Manhattan distance
BibRef
Wu, X.L.[Xiao-Ling],
Yu, Y.F.[Yu-Feng],
Chen, L.[Long],
Ding, W.P.[Wei-Ping],
Wang, Y.X.[Ying-Xu],
Robust deep fuzzy K-means clustering for image data,
PR(153), 2024, pp. 110504.
Elsevier DOI
2405
Locality preserving, Deep convolutional autoencoder,
Laplacian regularization, Unsupervised image clustering
BibRef
Heidari, J.,
Daneshpour, N.,
Zangeneh, A.,
A novel K-means and K-medoids algorithms for clustering
non-spherical-shape clusters non-sensitive to outliers,
PR(155), 2024, pp. 110639.
Elsevier DOI
2408
Initial centers, Number of clusters, Overlap space, Non-spherical
BibRef
Zhang, X.D.[Xiang-Dong],
Li, F.F.[Fang-Fang],
Shi, Z.Y.[Zhao-Yang],
Yang, M.[Ming],
Multi-view reduced dimensionality K-means clustering with sigma-norm
and Schatten p-norm,
PR(155), 2024, pp. 110675.
Elsevier DOI
2408
Multi-view, Dimensionality reduction, Matrix sigma-norm, Schatten p-norm
BibRef
Huang, X.[Xiuqi],
Tao, H.[Hong],
Ni, H.T.[Hao-Tian],
Hou, C.P.[Chen-Ping],
Debiasing weighted multi-view k-means clustering based on causal
regularization,
PR(160), 2025, pp. 111195.
Elsevier DOI
2501
Multi-view, Clustering, Covariate balance, Causal regularization
BibRef
Zhang, Z.T.[Zi-Tong],
Chen, X.J.[Xiao-Jun],
Wang, C.[Chen],
Wang, R.[Ruili],
Song, W.[Wei],
Nie, F.P.[Fei-Ping],
Structured multi-view k-means clustering,
PR(160), 2025, pp. 111113.
Elsevier DOI
2501
Clustering, Multi-view clustering, -means, Structure learning
BibRef
Pei, S.F.[Shen-Fei],
Sun, Y.C.[Yuan-Chen],
Nie, F.P.[Fei-Ping],
Jiang, X.D.[Xu-Dong],
Zheng, Z.W.[Zeng-Wei],
Adaptive Graph K-Means,
PR(161), 2025, pp. 111226.
Elsevier DOI
2502
Machine learning, Clustering, Graph-based, -means, Computational efficiency
BibRef
Huang, C.Y.[Cheng-Ying],
Wu, Z.[Zhengda],
Xi, H.[Heran],
Zhu, J.H.[Jing-Hua],
kMaXU: Medical image segmentation U-Net with k-means Mask Transformer
and contrastive cluster assignment,
PR(161), 2025, pp. 111274.
Elsevier DOI Code:
WWW Link.
2502
U-shaped network, Convolutional neural network,
Mask Transformer, Medical image segmentation, Cluster assignments
BibRef
Gao, Q.X.[Quan-Xue],
Li, F.F.[Fang-Fang],
Wang, Q.Q.[Qian-Qian],
Gao, X.B.[Xin-Bo],
Tao, D.C.[Da-Cheng],
Manifold Based Multi-View K-Means,
PAMI(47), No. 4, April 2025, pp. 3175-3182.
IEEE DOI
2503
Manifolds, Kernel, Tensors, Manifold learning, Estimation,
Nearest neighbor methods, Buildings, Accuracy, Vectors,
tensor schatten p-norm
BibRef
Yang, M.S.[Miin-Shen],
Sinaga, K.P.[Kristina P.],
Federated Multi-View K-Means Clustering,
PAMI(47), No. 4, April 2025, pp. 2446-2459.
IEEE DOI
2503
Clustering algorithms, Federated learning, Distributed databases,
Data models, Data privacy, Machine learning algorithms, Kernel,
privacy
BibRef
Meng, B.[Bin],
Li, F.F.[Fang-Fang],
Yang, F.[Fan],
Gao, Q.X.[Quan-Xue],
Centroid-Free K-Means With Balanced Clustering,
SPLetters(32), 2025, pp. 1191-1195.
IEEE DOI
2503
Clustering algorithms, Manifolds, Manifold learning,
Signal processing algorithms, Optimization, K-means
BibRef
Bajpai, N.[Namita],
Paik, J.H.[Jiaul H.],
Sarkar, S.[Sudeshna],
Balanced seed selection for K-means clustering with determinantal
point process,
PR(164), 2025, pp. 111548.
Elsevier DOI
2504
K-means, Determinantal point process
BibRef
Fu, Z.Q.[Zhi-Qiang],
Zhao, Y.[Yao],
Chang, D.X.[Dong-Xia],
Wang, Y.M.[Yi-Ming],
Wen, J.[Jie],
Reordered k-Means: A New Baseline for View-Unaligned Multi-View
Clustering,
MultMed(27), 2025, pp. 1962-1972.
IEEE DOI
2504
Clustering methods, Spatiotemporal phenomena,
Information science, Matrix converters, Image color analysis,
matrix factorization
BibRef
Zaech, J.N.[Jan-Nico],
Danelljan, M.[Martin],
Birdal, T.[Tolga],
Van Gool, L.J.[Luc J.],
Probabilistic Sampling of Balanced K-Means using Adiabatic Quantum
Computing,
CVPR24(26191-26201)
IEEE DOI
2410
Visualization, Quantum computing, Costs, Current measurement,
Posterior probability, Prototypes, Quantum Computing, Clustering,
uncertainty estimation
BibRef
Miao, S.Y.[Shu-Yu],
Zheng, L.[Lin],
Liu, J.J.[Jing-Jing],
Jin, H.[Hong],
K-means Clustering Based Feature Consistency Alignment for Label-free
Model Evaluation,
VDU23(3299-3307)
IEEE DOI
2309
BibRef
Lu, Y.H.[Yi-Hang],
Zheng, X.[Xuan],
Wang, R.[Rong],
Nie, F.P.[Fei-Ping],
Li, X.L.[Xue-Long],
A Unified Framework for Discrete Multi-kernel k-means with Kernel
Diversity Regularization,
ICPR22(4934-4940)
IEEE DOI
2212
Correlation, Diversity reception, Redundancy, Boosting,
Kernel, Task analysis
BibRef
Goel, A.[Anurag],
Majumdar, A.[Angshul],
Chouzenoux, E.[Emilie],
Chierchia, G.[Giovanni],
Deep Convolutional K-Means Clustering,
ICIP22(211-215)
IEEE DOI
2211
Deep learning, Training, Representation learning, Transforms,
Benchmark testing, Decoding, Convolutional Neural Network,
Convolutional Transform Learning
BibRef
Qian, Q.[Qi],
Xu, Y.H.[Yuan-Hong],
Hu, J.[Juhua],
Li, H.[Hao],
Jin, R.[Rong],
Unsupervised Visual Representation Learning by Online Constrained
K-Means,
CVPR22(16619-16628)
IEEE DOI
2210
Representation learning, Training, Visualization, Transformers,
Data structures, Computational efficiency,
Self- semi- meta- unsupervised learning
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Ren, Y.H.[Yuan-Hang],
Du, Y.[Ye],
Uniform and Non-uniform Sampling Methods for Sub-linear Time k-means
Clustering,
ICPR21(7775-7781)
IEEE DOI
2105
Image segmentation, Machine learning algorithms,
Clustering algorithms, Machine learning,
BibRef
Fukunaga, T.[Takumi],
Kasai, H.[Hiroyuki],
Wasserstein k-means with sparse simplex projection,
ICPR21(1627-1634)
IEEE DOI
2105
Degradation, Histograms, Heuristic algorithms,
Clustering algorithms, Sparse matrices, Proposals
BibRef
Chen, Q.,
Jiang, J.,
Du, M.,
Zhou, L.,
Jing, C.,
Lu, C.,
A Hybridization of An Improved Particle Swarm Optimization and Fuzzy
K-means Algorithm for Hyperspectral Image Classification,
HyperMLPA19(1833-1839).
DOI Link
1912
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Le, H.M.[Huu M.],
Eriksson, A.P.[Anders P.],
Do, T.T.[Thanh-Toan],
Milford, M.[Michael],
A Binary Optimization Approach for Constrained K-Means Clustering,
ACCV18(IV:383-398).
Springer DOI
1906
BibRef
Cai, G.,
Zhang, R.,
Nie, F.,
Li, X.,
Feature Selection via Incorporating Stiefel Manifold in Relaxed
K-Means,
ICIP18(1503-1507)
IEEE DOI
1809
Feature extraction, Manifolds, Clustering algorithms,
Approximation algorithms, Eigenvalues and eigenfunctions, Graph embedded
BibRef
Rastogi, R.[Reshma],
Sharma, S.[Sweta],
Tree-Based Structural Twin Support Tensor Clustering with Square Loss
Function,
PReMI17(28-34).
Springer DOI
1711
BibRef
Kumar, R.[Ritesh],
Bishnu, P.S.[Partha Sarathi],
Bhattacherjee, V.[Vandana],
K-Means Algorithm to Identify k1-Most Demanding Products,
PReMI17(451-457).
Springer DOI
1711
BibRef
Fatima, E.B.,
Abdelmajid, E.M.,
Study of efficiency k-means clustering using Z-test proprieties,
ISCV17(1-5)
IEEE DOI
1710
data mining, fuzzy set theory,
pattern clustering, K-means algorithm, Z value, Z-test proprieties,
efficiency k-means clustering, input data points,
Clustering algorithms, Complexity theory, Data mining, Sociology,
Z-test, clustering, data mining, k, means
BibRef
Ye, Y.K.[Yong-Kai],
Liu, X.,
Yin, J.,
Zhu, E.,
Co-regularized kernel k-means for multi-view clustering,
ICPR16(1583-1588)
IEEE DOI
1705
Algorithm design and analysis, Clustering algorithms,
Eigenvalues and eigenfunctions, Iterative methods, Kernel,
Optimization, Training
BibRef
Xu, J.L.[Jing-Lin],
Han, J.W.[Jun-Wei],
Nie, F.P.[Fei-Ping],
Discriminatively Embedded K-Means for Multi-view Clustering,
CVPR16(5356-5364)
IEEE DOI
1612
BibRef
Luchi, D.[Diego],
Santos, W.[Willian],
Rodrigues, A.[Alexandre],
Varejão, F.M.[Flávio Miguel],
Genetic Sampling k-means for Clustering Large Data Sets,
CIARP15(691-698).
Springer DOI
1511
BibRef
Choi, Y.K.[Yu-Kyung],
Park, C.[Chaehoon],
Kweon, I.S.[In So],
Accelerated Kmeans Clustering Using Binary Random Projection,
ACCV14(II: 257-272).
Springer DOI
1504
BibRef
Fu, X.[Xiping],
McCane, B.[Brendan],
Mills, S.[Steven],
Albert, M.[Michael],
NOKMeans: Non-Orthogonal K-means Hashing,
ACCV14(I: 162-177).
Springer DOI
1504
BibRef
Yu, Z.D.[Zhi-Ding],
Xu, C.J.[Chun-Jing],
Meng, D.Y.[De-Yu],
Hui, Z.[Zhuo],
Xiao, F.Y.[Fan-Yi],
Liu, W.B.[Wen-Bo],
Liu, J.Z.[Jian-Zhuang],
Transitive Distance Clustering with K-Means Duality,
CVPR14(987-994)
IEEE DOI
1409
BibRef
Aroche-Villarruel, A.A.[Argenis A.],
Carrasco-Ochoa, J.A.,
Martínez-Trinidad, J.F.[José Francisco],
Olvera-López, J.A.[J. Arturo],
Pérez-Suárez, A.[Airel],
Study of Overlapping Clustering Algorithms Based on Kmeans through
FBcubed Metric,
MCPR14(112-121).
Springer DOI
1407
BibRef
Nakouri, H.[Haïfa],
Limam, M.[Mohamed],
Automatic Feature Detection and Clustering Using Random Indexing,
ICISP14(586-593).
Springer DOI
1406
BibRef
Earlier:
Discovering Features Contexts from Images Using Random Indexing,
IWCIA14(134-145).
Springer DOI
1405
BibRef
Li, Q.[Qun],
Qin, Z.[Zhen],
Chai, L.S.[Lun-Shao],
Zhang, H.G.[Hong-Gang],
Guo, J.[Jun],
Bhanu, B.[Bir],
Representative reference-set and betweenness centrality for scene
image categorization,
ICIP13(3254-3258)
IEEE DOI
1402
K-means
BibRef
Norouzi, M.[Mohammad],
Fleet, D.J.[David J.],
Cartesian K-Means,
CVPR13(3017-3024)
IEEE DOI
1309
approximate nearest neighbor search
BibRef
He, K.[Kaiming],
Wen, F.[Fang],
Sun, J.[Jian],
K-Means Hashing: An Affinity-Preserving Quantization Method for
Learning Binary Compact Codes,
CVPR13(2938-2945)
IEEE DOI
1309
binary embedding; hash; nearest neighbor search
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Havens, T.C.[Timothy C.],
Approximation of kernel k-means for streaming data,
ICPR12(509-512).
WWW Link.
1302
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Li, Z.Y.[Ze-Yu],
Vinyals, O.[Oriol],
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Feature learning using Generalized Extreme Value distribution based
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ICPR12(1538-1541).
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Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
ISODATA Clustering .