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2006
IEEE
15 years 6 months ago
Matrix Multiplication on Two Interconnected Processors
This paper presents a new partitioning algorithm to perform matrix multiplication on two interconnected heterogeneous processors. Data is partitioned in a way which minimizes the ...
Brett A. Becker, Alexey L. Lastovetsky
PODS
2008
ACM
159views Database» more  PODS 2008»
15 years 12 months ago
Approximation algorithms for clustering uncertain data
There is an increasing quantity of data with uncertainty arising from applications such as sensor network measurements, record linkage, and as output of mining algorithms. This un...
Graham Cormode, Andrew McGregor
GECCO
2006
Springer
144views Optimization» more  GECCO 2006»
15 years 3 months ago
On semi-supervised clustering via multiobjective optimization
Semi-supervised classification uses aspects of both unsupervised and supervised learning to improve upon the performance of traditional classification methods. Semi-supervised clu...
Julia Handl, Joshua D. Knowles
BMCBI
2007
156views more  BMCBI 2007»
14 years 12 months ago
Large-scale clustering of CAGE tag expression data
Background: Recent analyses have suggested that many genes possess multiple transcription start sites (TSSs) that are differentially utilized in different tissues and cell lines. ...
Kazuro Shimokawa, Yuko Okamura-Oho, Takio Kurita, ...
ICCV
2009
IEEE
1556views Computer Vision» more  ICCV 2009»
16 years 4 months ago
Kernel Methods for Weakly Supervised Mean Shift Clustering
Mean shift clustering is a powerful unsupervised data analysis technique which does not require prior knowledge of the number of clusters, and does not constrain the shape of th...
Oncel Tuzel, Fatih Porikli, Peter Meer