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