Mittagsseminar (in cooperation with A. Steger, D. Steurer and B. Sudakov)

Date and Time: Thursday, January 22, 2004, 12:15 pm

Duration: This information is not available in the database

Location: This information is not available in the database

Speaker: Julian Lorenz

Geometric Clustering Problems

In this talk I will present my diploma thesis on "geometric clustering problems". We will consider two different models, namely k-Clustering and minsum-Clustering. Given n points in R^d, in k-clustering the problem is to find k clusters such that the sum of squared distances of each data point to the center of its cluster is minimized. We will focus on the case when the dimension d is part of the input, and use a dimension reduction technique by Johnson-Lindenstrauss to improve known algorithms. In minsum-clustering the problem is to minimize the sum of all distances between points in the same cluster. I will present an approximation approach by iterative matchings, and give some partial results about its approximation behaviour.

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