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ISAAC
2009
Springer
175views Algorithms» more  ISAAC 2009»
15 years 4 months ago
Worst-Case and Smoothed Analysis of k-Means Clustering with Bregman Divergences
The k-means algorithm is the method of choice for clustering large-scale data sets and it performs exceedingly well in practice. Most of the theoretical work is restricted to the c...
Bodo Manthey, Heiko Röglin
IEEEPACT
2000
IEEE
15 years 2 months ago
Instruction Scheduling for Clustered VLIW DSPs
Recent digital signal processors (DSPs) show a homogeneous VLIW-like data path architecture, which allows C compilers to generate efficient code. However, still some special rest...
Rainer Leupers
SASP
2009
IEEE
170views Hardware» more  SASP 2009»
15 years 4 months ago
Parade: A versatile parallel architecture for accelerating pulse train clustering
— In this paper, we present Parade, a novel and flexible parallel architecture for the deinterleaving of combined pulsetrains. This is a commonly performed task in various areas ...
Amin Ansari, Dan Zhang, Scott A. Mahlke
HICSS
2008
IEEE
199views Biometrics» more  HICSS 2008»
15 years 4 months ago
Clustering and the Biclique Partition Problem
A technique for clustering data by common attribute values involves grouping rows and columns of a binary matrix to make the minimum number of submatrices all 1’s. As binary mat...
Doina Bein, Linda Morales, Wolfgang W. Bein, C. O....
SEMCO
2008
IEEE
15 years 4 months ago
SEMSOC: SEMantic, SOcial and Content-Based Clustering in Multimedia Collaborative Tagging Systems
A huge amount of data and metadata emerges from Web 2.0 applications which have transformed the Web to a mass social interaction and collaboration medium. Collaborative Tagging Sy...
Eirini Giannakidou, Ioannis Kompatsiaris, Athena V...