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» Optimizing for parallelism and data locality
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CORR
2008
Springer
76views Education» more  CORR 2008»
15 years 23 days ago
Communication-avoiding parallel and sequential QR factorizations
We present parallel and sequential dense QR factorization algorithms that are optimized to avoid communication. Some of these are novel, and some extend earlier work. Communicatio...
James Demmel, Laura Grigori, Mark Hoemmen, Julien ...
ICPR
2002
IEEE
16 years 1 months ago
Unsupervised Learning Using Locally Linear Embedding: Experiments with Face Pose Analysis
This paper considers a recently proposed method for unsupervised learning and dimensionality reduction, locally linear embedding (LLE). LLE computes a compact representation of hi...
Abdenour Hadid, Matti Pietikäinen, Olga Kouro...
205
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VLDB
2007
ACM
145views Database» more  VLDB 2007»
16 years 27 days ago
Executing Stream Joins on the Cell Processor
Low-latency and high-throughput processing are key requirements of data stream management systems (DSMSs). Hence, multi-core processors that provide high aggregate processing capa...
Bugra Gedik, Philip S. Yu, Rajesh Bordawekar
MICCAI
2008
Springer
16 years 1 months ago
Rician Noise Removal by Non-Local Means Filtering for Low Signal-to-Noise Ratio MRI: Applications to DT-MRI
Diffusion-Weighted MRI (DW-MRI) is subject to random noise yielding measures that are different from their real values, and thus biasing the subsequently estimated tensors. The Non...
Nicolas Wiest-Daesslé, Sylvain Prima, Pierr...
PKDD
2009
Springer
120views Data Mining» more  PKDD 2009»
15 years 7 months ago
Variational Graph Embedding for Globally and Locally Consistent Feature Extraction
Existing feature extraction methods explore either global statistical or local geometric information underlying the data. In this paper, we propose a general framework to learn fea...
Shuang-Hong Yang, Hongyuan Zha, Shaohua Kevin Zhou...