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147
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ICS
2010
Tsinghua U.
15 years 6 months ago
Clustering performance data efficiently at massive scales
Existing supercomputers have hundreds of thousands of processor cores, and future systems may have hundreds of millions. Developers need detailed performance measurements to tune ...
Todd Gamblin, Bronis R. de Supinski, Martin Schulz...
MICCAI
2004
Springer
16 years 4 months ago
A Data Clustering and Streamline Reduction Method for 3D MR Flow Vector Field Simplification
Abstract. With the increasing capability of MR imaging and Computational Fluid Dynamics (CFD) techniques, a significant amount of data related to the haemodynamics of the cardiovas...
Bernardo Silva Carmo, Yin-Heung Pauline Ng, Adam P...
141
Voted
TASLP
2008
120views more  TASLP 2008»
15 years 3 months ago
Rapid Speaker Adaptation Using Clustered Maximum-Likelihood Linear Basis With Sparse Training Data
Abstract-- Speaker space based adaptation methods for automatic speech recognition have been shown to provide significant performance improvements for tasks where only a few second...
Yun Tang, Richard Rose
153
Voted
TIP
2010
131views more  TIP 2010»
14 years 10 months ago
Orientation Modulation for Data Hiding in Clustered-Dot Halftone Prints
We present a new framework for data hiding in images printed with clustered dot halftones. Our application scenario, like other hardcopy embedding methods, encounters fundamental c...
Orhan Bulan, Gaurav Sharma, Vishal Monga
118
Voted
ACMSE
2007
ACM
15 years 7 months ago
Verifying design modularity, hierarchy, and interaction locality using data clustering techniques
Modularity, hierarchy, and interaction locality are general approaches to reducing the complexity of any large system. A widely used principle in achieving these goals in designin...
Liguo Yu, Srini Ramaswamy