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» A New Selection Ratio for Large Population Sizes
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IEEEPACT
2005
IEEE
14 years 9 days ago
Trace Cache Sampling Filter
This paper presents a new technique for efficient usage of small trace caches. A trace cache can significantly increase the performance of wide out-oforder processors, but to be e...
Michael Behar, Avi Mendelson, Avinoam Kolodny
GECCO
2008
Springer
137views Optimization» more  GECCO 2008»
13 years 7 months ago
Informative sampling for large unbalanced data sets
Selective sampling is a form of active learning which can reduce the cost of training by only drawing informative data points into the training set. This selected training set is ...
Zhenyu Lu, Anand I. Rughani, Bruce I. Tranmer, Jos...
TON
2010
125views more  TON 2010»
13 years 1 months ago
S4: Small State and Small Stretch Compact Routing Protocol for Large Static Wireless Networks
Routing protocols for large wireless networks must address the challenges of reliable packet delivery at increasingly large scales and with highly limited resources. Attempts to re...
Y. Mao, F. Wang, L. Qiu, S. Lam, J. Smith
NSDI
2007
13 years 9 months ago
S4: Small State and Small Stretch Routing Protocol for Large Wireless Sensor Networks
Routing protocols for wireless sensor networks must address the challenges of reliable packet delivery at increasingly large scale and highly constrained node resources. Attempts ...
Yun Mao, Feng Wang, Lili Qiu, Simon S. Lam, Jonath...
EMNLP
2009
13 years 4 months ago
Less is More: Significance-Based N-gram Selection for Smaller, Better Language Models
The recent availability of large corpora for training N-gram language models has shown the utility of models of higher order than just trigrams. In this paper, we investigate meth...
Robert C. Moore, Chris Quirk