Displaying similar documents to “How the initialization affects the stability of the қ-means algorithm”

How the initialization affects the stability of the қ-means algorithm

Sébastien Bubeck, Marina Meilă, Ulrike von Luxburg (2012)

ESAIM: Probability and Statistics

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We investigate the role of the initialization for the stability of the қ-means clustering algorithm. As opposed to other papers, we consider the actual қ-means algorithm (also known as Lloyd algorithm). In particular we leverage on the property that this algorithm can get stuck in local optima of the қ-means objective function. We are interested in the actual clustering, not only in the costs of the solution. We analyze when different ...

Extending the MAX Algorithm for Maximum Independent Set

Ngoc C. Lê, Christoph Brause, Ingo Schiermeyer (2015)

Discussiones Mathematicae Graph Theory

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The maximum independent set problem is an NP-hard problem. In this paper, we consider Algorithm MAX, which is a polynomial time algorithm for finding a maximal independent set in a graph G. We present a set of forbidden induced subgraphs such that Algorithm MAX always results in finding a maximum independent set of G. We also describe two modifications of Algorithm MAX and sets of forbidden induced subgraphs for the new algorithms.

Parallelization of artificial immune systems using a massive parallel approach via modern GPUs

Khun, Jiří, Šimeček, Ivan

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Parallelization is one of possible approaches for obtaining better results in terms of algorithm performance and overcome the limits of the sequential computation. In this paper, we present a study of parallelization of the opt-aiNet algorithm which comes from Artificial Immune Systems, one part of large family of population based algorithms inspired by nature. The opt-aiNet algorithm is based on an immune network theory which incorporates knowledge about mammalian immune systems in...