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Krahasoni metodat

Shqyrtoni metodat e zgjedhura krah për krah; rreshtat që ndryshojnë janë të theksuar.

K-means vetë-mbikëqyrës×K-means Online×
FushaMësimi i makinësMësimi i makinës
FamiljaMachine learningMachine learning
Viti i origjinës20181967 (online update rule); 2010 (mini-batch variant)
KrijuesiCaron, M. et al. (DeepCluster framework)MacQueen, J. (batch); Sculley, D. (mini-batch web-scale variant)
LlojiSelf-supervised clusteringUnsupervised clustering (online/streaming)
Burimi themeluesCaron, M., Bojanowski, P., Joulin, A., & Douze, M. (2018). Deep Clustering for Unsupervised Learning of Visual Features. In Proceedings of the European Conference on Computer Vision (ECCV), 132–149. link ↗MacQueen, J. (1967). Some methods for classification and analysis of multivariate observations. In Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, Vol. 1, pp. 281–297. University of California Press. link ↗
Emërtime të tjeraself-supervised clustering with K-means, deep clustering with K-means, unsupervised K-means with pseudo-labels, SSL K-meanssequential k-means, streaming k-means, incremental k-means, online clustering
Të lidhura54
PërmbledhjaSelf-supervised K-means is a clustering technique that combines K-means assignment with self-supervised representation learning. The model alternates between clustering unlabeled data points into K groups and using those cluster assignments as pseudo-labels to refine an underlying feature representation, yielding increasingly coherent clusters without any human-annotated ground truth.Online K-means is a streaming variant of the classical K-means algorithm that updates cluster centroids one observation at a time — or in small mini-batches — without storing the entire dataset in memory. It is particularly suited to large-scale, real-time, or continuously arriving data where batch recomputation would be too slow or impractical.
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ScholarGateKrahasoni metodat: Self-supervised K-means · Online K-means. Marrë më 2026-06-18 nga https://scholargate.app/sq/compare