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» Massive Data Pre-Processing with a Cluster Based Approach
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DAC
2001
ACM
16 years 5 months ago
Clustered VLIW Architectures with Predicated Switching
In order to meet the high throughput requirements of applications exhibiting high ILP, VLIW ASIPs may increasingly include large numbers of functional unitsFUs. Unfortunately, `sw...
Margarida F. Jacome, Gustavo de Veciana, Satish Pi...
PR
2006
127views more  PR 2006»
15 years 4 months ago
Unsupervised possibilistic clustering
In fuzzy clustering, the fuzzy c-means (FCM) clustering algorithm is the best known and used method. Since the FCM memberships do not always explain the degrees of belonging for t...
Miin-Shen Yang, Kuo-Lung Wu
124
Voted
GRAPHITE
2004
ACM
15 years 9 months ago
Understanding next-generation VR: classifying commodity clusters for immersive virtual reality
Commodity clusters offer the ability to deliver higher performance computer graphics at lower prices than traditional graphics supercomputers. Immersive virtual reality systems de...
Alexander Streit, Ruth Christie, Andy Boud
UAI
2003
15 years 5 months ago
Probabilistic Models For Joint Clustering And Time-Warping Of Multidimensional Curves
In this paper we present a family of models and learning algorithms that can simultaneously align and cluster sets of multidimensional curves measured on a discrete time grid. Our...
Darya Chudova, Scott Gaffney, Padhraic Smyth
146
Voted
FPL
2006
Springer
125views Hardware» more  FPL 2006»
15 years 7 months ago
Application-Specific Memory Interleaving for FPGA-Based Grid Computations: A General Design Technique
Many compute-intensive applications generate single result values by accessing clusters of nearby points in grids of one, two, or more dimensions. Often, the performance of FGPA i...
Tom Van Court, Martin C. Herbordt