Multicasting large amounts of data efficiently to all nodes of a PC cluster is an important operation. In the form of a partition cast it can be used to replicate entire software installations by cloning. Optimizing a partition cast for a given cluster of PCs reveals some interesting architectural tradeoffs, since the fastest solution does not only depend on the network speed and topology, but ...

A new approach is presented for clustering the speakers from unlabeled and unsegmented conversation, when the number of speakers is unknown. In this approach, each speaker is modeled by a SelfOrganizing-Map (SOM). For estimation of the number of clusters the Bayesian Information Criterion (BIC) is applied. This approach was tested on the NIST 1996 HUB-4 evaluation test in terms of speaker and c...

We propose a novel class of kernels to identify tactical patterns in multi-trajectory data such as soccer games. Formally, we introduce a group of R-convolution kernels called Spatio-Temporal Convolution Kernels composed of a temporal and a spatial kernel. The particular choice of the component kernels depends on the application at hand. For the purpose of clustering player and ball trajectorie...

The paper examines how adjectival modification classes can be detected by applying unsupervised methods on adjective-noun co-occurrence data. It evaluates a k-means baseline, two graphical models, and a recently introduced bidirectional clustering algorithm against HeiPLAS, a manually annotated gold standard for hidden modificational classes. The paper shows that the bidirectional clustering al...

The performance of writer-independent unconstrained handwriting recognition is severely affected by variations in writing style. In a segmentation-free approach based on Hidden-Markov models we, therefore, use multiple recognition models specialized to specific writing styles in order to improve recognition performance. As the explicit definition of writing styles is not obvious we propose an u...

The NIH Library of Integrated Network-based Cellular Signatures (LINCS) contains gene expression data from over a million experiments, using Luminex Bead technology. Only 500 colors are used to measure the expression levels of the 1,000 landmark genes measured, and the data for the resulting pairs of genes are deconvolved. The raw data are sometimes inadequate for reliable deconvolution leading...

We propose two new measures for evaluating offensive ability of NBA players, using onedimensional shooting data from three seasons beginning with the 2004-05 season. These measures improve upon currently employed shooting statistics by accounting for the varying shooting patterns of players over different distances from the basket. This variance also provides us with an intuitive metric for clu...

Projection algorithms such as multidimensional scaling are often used to visualize high-dimensional data. However, when attempting to interpret the visualization of the resulting 2D projection, users are faced with artifacts. This poster introduces ProxiViz: an interactive technique to provide better insights about the original data-space. Primary results of a controlled experiment show that Pr...

This paper presents a cluster approach to the calculation of the g factors for 3d7 ions in cubic oc­ tahedral crystals, in which the parameters related to the configuration interaction and the covalency reduction effects are obtained from optical spectra of the studied crystals, and so no adjustable parameters are applied. From the approach, the g factors for MgO:Co2+ and CaO:Co2+ are cal­ cula...

Multi-Agent Data Mining (MADM) seeks to harness the general advantages offered by Multi-Agent System (MAS) with respect to the domain of data mining. The research described in this thesis is concerned with Multi-Agent Based Clustering (MABC), thus MADM to support clustering. To investigate the use of MAS technology with respect to data mining, and specifically data clustering, two approaches ar...