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MatrixNet

From Wikipedia, the free encyclopedia

MatrixNet is a proprietary machine learning algorithm developed by Yandex and used widely throughout the company products. The algorithm is based on gradient boosting, and was introduced since 2009.[1][2]

Application

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CERN is using the algorithm to analyze, and search through the colossal data outputs generated by the use of the Large Hadron Collider.[3]

See also

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References

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