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

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

References

  1. ^ MatrixNet: New Level of Search Quality. Retrieved 2015-12-24.
  2. ^ Yandex Boosts Precision Ad Targeting; Machine-Learning Method MatrixNet Is Behind The Scenes. Retrieved 2015-12-24.
  3. ^ CERN boosts its search for antimatter with Yandex’s MatrixNet search engine tech. Retrieved 2015-12-24.
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