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» Clustering performance data efficiently at massive scales
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121
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TIP
2010
165views more  TIP 2010»
14 years 7 months ago
Physically Consistent and Efficient Variational Denoising of Image Fluid Flow Estimates
Imaging plays an important role in experimental fluid dynamics. It is equally important both for scientific research and a range of industrial applications. It is known, however, t...
Andrey Vlasenko, Christoph Schnörr
120
Voted
KDD
2005
ACM
153views Data Mining» more  KDD 2005»
16 years 1 months ago
Using retrieval measures to assess similarity in mining dynamic web clickstreams
While scalable data mining methods are expected to cope with massive Web data, coping with evolving trends in noisy data in a continuous fashion, and without any unnecessary stopp...
Olfa Nasraoui, Cesar Cardona, Carlos Rojas
106
Voted
DAWAK
2003
Springer
15 years 6 months ago
Handling Large Workloads by Profiling and Clustering
View materialization is recognized to be one of the most effective ways to increase the Data Warehouse performance; nevertheless, due to the computational complexity of the techniq...
Matteo Golfarelli
92
Voted
APVIS
2008
15 years 2 months ago
ZAME: Interactive Large-Scale Graph Visualization
We present the Zoomable Adjacency Matrix Explorer (ZAME), a visualization tool for exploring graphs at a scale of millions of nodes and edges. ZAME is based on an adjacency matrix...
Niklas Elmqvist, Thanh-Nghi Do, Howard Goodell, Na...
CVPR
2001
IEEE
16 years 2 months ago
Light Field Rendering for Large-Scale Scenes
In this paper, we present an efficient method to synthesize large-scale scenes, such as broad city landscapes. To date, model based approaches have mainly been adopted for this pu...
Hiroshi Kawasaki, Katsushi Ikeuchi, Masao Sakauchi