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- W2018349711 abstract "Various techniques exist to solve the non-convex optimization problem of clustering. Recent developments have employed a deterministic annealing approach to solving this problem. In this letter a new approximation clustering algorithm, incorporating a gradient descent technique with deterministic annealing, is described. Results are presented for this new method, and its performance is compared with the K-means algorithm and a previously used deterministic annealing clustering algorithm. The new method is shown to produce more effective and robust clustering." @default.
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- W2018349711 title "Improved clustering using deterministic annealing with a gradient descent technique" @default.
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- W2018349711 doi "https://doi.org/10.1016/0167-8655(94)90021-3" @default.
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