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WSC
2004
13 years 9 months ago
Data Farming: Discovering Surprise
Data Farming is a methodology and capability that makes use of high performance computing to run models many times. This capability gives modelers and their clients the enhanced a...
Gary E. Horne, Theodore E. Meyer
CIKM
2010
Springer
13 years 6 months ago
Decomposing background topics from keywords by principal component pursuit
Low-dimensional topic models have been proven very useful for modeling a large corpus of documents that share a relatively small number of topics. Dimensionality reduction tools s...
Kerui Min, Zhengdong Zhang, John Wright, Yi Ma
PAMI
2012
11 years 10 months ago
Quantifying and Transferring Contextual Information in Object Detection
— Context is critical for reducing the uncertainty in object detection. However, context modelling is challenging because there are often many different types of contextual infor...
Wei-Shi Zheng, Shaogang Gong, Tao Xiang
ICSE
2009
IEEE-ACM
14 years 9 months ago
Reasoning about edits to feature models
Features express the variabilities and commonalities among programs in a software product line (SPL). A feature model defines the valid combinations of features, where each combin...
Christian Kästner, Don S. Batory, Thomas Th&u...
VLSID
2008
IEEE
95views VLSI» more  VLSID 2008»
14 years 8 months ago
A New Threshold Voltage Model for Omega Gate Cylindrical Nanowire Transistor
In this work, for the first time, we present a physically based analytical threshold voltage model for omega gate silicon nanowire transistor. This model is developed for long cha...
Biswajit Ray, Santanu Mahapatra