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Randomness extractor

Known as: Extractor, Von Neumann extractor 
A randomness extractor, often simply called an "extractor", is a function, which being applied to output from a weakly random entropy source… Expand
Wikipedia

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Review
2019
Review
2019
With the breakthroughs in deep learning, the recent years have witnessed a booming of artificial intelligence (AI) applications… Expand
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Review
2018
Review
2018
Vortices are commonly understood as rotating motions in fluid flows. The analysis of vortices plays an important role in numerous… Expand
Review
2018
Review
2018
We present a neural framework for opinion summarization from online product reviews which is knowledge-lean and only requires… Expand
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Review
2017
Review
2017
Several methods of extraction and analytical determination for total petroleum hydrocarbons (TPHCs) in aqueous and solid samples… Expand
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Highly Cited
2017
Highly Cited
2017
Feature pyramids are a basic component in recognition systems for detecting objects at different scales. But pyramid… Expand
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Highly Cited
2014
Highly Cited
2014
We present an integrated framework for using Convolutional Networks for classification, localization and detection. We show how a… Expand
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Highly Cited
2010
Highly Cited
2010
We introduce the openSMILE feature extraction toolkit, which unites feature extraction algorithms from the speech processing and… Expand
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Highly Cited
2008
Highly Cited
2008
We give an improved explicit construction of highly unbalanced bipartite expander graphs with expansion arbitrarily close to the… Expand
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Highly Cited
2006
Highly Cited
2006
We describe a novel unsupervised method for learning sparse, overcomplete features. The model uses a linear encoder, and a linear… Expand
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Highly Cited
2000
Highly Cited
2000
The standard notion of a randomness extractor is a procedure which converts any weak source of randomness into an almost uniform… Expand