A Computational Comparison of Parallel and Distributed K-median Clustering Algorithms on Large-Scale Image Data

Ushakov, Anton V.; Vasilyev, Igor

doi:10.1007/978-3-030-33394-2_10

Cited by 2 publications

(2 citation statements)

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“…The use of evolutionary algorithms (e.g. genetic ones) is a common approach to improve the local search results [5,21]. They usually recombine the solutions obtained using the ALA procedure.To estimate the final value (local minimum) of the sum of distances (1), the GA at each iteration uses the ALA procedure or a local search algorithm.…”

Section: Known Approachesmentioning

confidence: 99%

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Hybrid algorithms with alternative embedded local search schemes for the p-median problem

Rezova,

Kazakovtsev,

Rozhnov

et al. 2023

IJITS JOURNAL

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Progress in the development of location theory and clustering methods is mainly aimed at improving the performance of algorithms. We study the continuous p-median problem with the Euclidean metric. Various algorithmic combinations of the ALA procedure embedded into more sophisticated algorithmic combinations are used. Two repeated steps of the ALA algorithm solve the simplest discrete optimization problem, and then a series of central point search problems (Weber problem) for each cluster. A parallel implementation of the ALA algorithm is used. The paper studies the issue of choosing from two strategies: solve the Weber problem until accuracy ε is achieved at each iteration, or perform only one iteration of the Weiszfeld algorithm at each ALA iteration.

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Section: Known Approachesmentioning

confidence: 99%

“…This fact increases the popularity of the k-means model. However, unlike the p-median, the k-means model is highly sensitive to the outliers (separately located points in a dataset) [5].…”

Section: Introductionmentioning

confidence: 99%