Dimension reduction

Count sketch

Count sketch is a type of dimensionality reduction that is particularly efficient in statistics, machine learning and algorithms.It was invented by Moses Charikar, Kevin Chen and Martin Farach-Colton in an effort to speed up the by Alon, Matias and Szegedy for approximating the frequency moments of streams. The sketch is nearly identical to the Feature hashing algorithm by John Moody, but differs in its use of hash functions with low dependence, which makes it more practical.In order to still have a high probability of success, the is used to aggregate multiple count sketches, rather than the mean. These properties allow use for explicit kernel methods, bilinear pooling in neural networks and is a cornerstone in many numerical linear algebra algorithms. (Wikipedia).

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From playlist Microsoft Excel tutorials

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From playlist Shorter videos

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From playlist Excel Series: Magic Tricks (4th 200 videos)

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From playlist 2016-T1 - Nexus of Information and Computation Theory - CEB Trimester

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From playlist Geometer's Sketchpad

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From playlist Statistics Playlist 1

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From playlist Nexus Trimester - 2016 - Central Workshop

Related pages

Feature hashing | Kronecker product | Dimensionality reduction | Khatri–Rao product | Neural network | Count–min sketch | Convolution | Statistics | Outer product | Fast Fourier transform