Displaying similar documents to “An approximate L p difference algorithm for massive data streams.”

Interpretation and optimization of the k -means algorithm

Kristian Sabo, Rudolf Scitovski (2014)

Applications of Mathematics

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The paper gives a new interpretation and a possible optimization of the well-known k -means algorithm for searching for a locally optimal partition of the set 𝒜 = { a i ∈ ℝ n : i = 1 , ⋯ , m } which consists of k disjoint nonempty subsets π 1 , ⋯ , π k , 1 ≤ k ≤ m . For this purpose, a new divided k -means algorithm was constructed as a limit case of the known smoothed k -means algorithm. It is shown that the algorithm constructed in this way coincides with the k -means algorithm if during the iterative procedure no data points appear in the...

Measuring the problem-relevant information in input

Stefan Dobrev, Rastislav Královič, Dana Pardubská (2009)

RAIRO - Theoretical Informatics and Applications

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We propose a new way of characterizing the complexity of online problems. Instead of measuring the degradation of the output quality caused by the ignorance of the future we choose to quantify the amount of additional global information needed for an online algorithm to solve the problem optimally. In our model, the algorithm cooperates with an oracle that can see the whole input. We define the advice complexity of the problem to be the minimal number of bits (normalized per input request,...