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TJS
2010
145views more  TJS 2010»
15 years 1 months ago
Analyzing and enhancing the parallel sort operation on multithreaded architectures
The Sort operation is a core part of many critical applications. Despite the large efforts to parallelize it, the fact that it suffers from high data-dependencies vastly limits it...
Layali K. Rashid, Wessam Hassanein, Moustafa A. Ha...
TNN
2010
176views Management» more  TNN 2010»
15 years 1 months ago
Sparse approximation through boosting for learning large scale kernel machines
Abstract--Recently, sparse approximation has become a preferred method for learning large scale kernel machines. This technique attempts to represent the solution with only a subse...
Ping Sun, Xin Yao
TVLSI
2010
15 years 1 months ago
Test Data Compression Using Efficient Bitmask and Dictionary Selection Methods
Abstract--Higher circuit densities in system-on-chip (SOC) designs have led to drastic increase in test data volume. Larger test data size demands not only higher memory requiremen...
Kanad Basu, Prabhat Mishra
JAISE
2011
179views more  JAISE 2011»
14 years 9 months ago
A hybrid probabilistic neural model for person tracking based on a ceiling-mounted camera
Person tracking is an important topic in ambient living systems as well as in computer vision. In particular, detecting a person from a ceiling-mounted camera is a challenge since ...
Wenjie Yan, Cornelius Weber, Stefan Wermter
SDM
2012
SIAM
237views Data Mining» more  SDM 2012»
13 years 9 months ago
A Distributed Kernel Summation Framework for General-Dimension Machine Learning
Kernel summations are a ubiquitous key computational bottleneck in many data analysis methods. In this paper, we attempt to marry, for the first time, the best relevant technique...
Dongryeol Lee, Richard W. Vuduc, Alexander G. Gray