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Cross entropy

Known as: Cross-entropy, Log loss, Minxent 
In information theory, the cross entropy between two probability distributions and over the same underlying set of events measures the average number… Expand
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Papers overview

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Review
2019
Review
2019
Abstract Online product reviews (OPRs) provide abundant information for potential customers to make optimal purchase decisions… Expand
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Review
2018
Review
2018
Existing text generation methods tend to produce repeated and “boring” expressions. To tackle this problem, we propose a new text… Expand
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Highly Cited
2006
Highly Cited
2006
In recent years, the cross-entropy method has been successfully applied to a wide range of discrete optimization tasks. In this… Expand
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Highly Cited
2001
Highly Cited
2001
The problem in estimating a social accounting matrix (SAM) for a recent year is to find an efficient and cost-effective way to… Expand
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Highly Cited
1998
Highly Cited
1998
  • C. Li, P. Tam
  • Pattern Recognit. Lett.
  • 1998
  • Corpus ID: 1881544
A fast iterative method is derived for minimum cross entropy thresholding using a one-point iteration scheme. Simulations… Expand
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Highly Cited
1996
Highly Cited
1996
  • N. Pal
  • Pattern Recognit.
  • 1996
  • Corpus ID: 26167340
Over last few years several papers have been written on entropy-based thresholding. Some of these methods use the gray-level… Expand
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Highly Cited
1996
Highly Cited
1996
Thresholding is a common and easily implemented form of image segmentation. Many methods of automatic threshold selection based… Expand
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Highly Cited
1993
Highly Cited
1993
Abstract The threshold selection problem is solved by minimizing the cross entropy between the image and its segmented version… Expand
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Highly Cited
1981
Highly Cited
1981
The principle of minimum cross-entropy (minimum directed divergence, minimum discrimination information) is a general method of… Expand
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Highly Cited
1980
Highly Cited
1980
Jaynes's principle of maximum entropy and Kullbacks principle of minimum cross-entropy (minimum directed divergence) are shown to… Expand
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