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.
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
MatrixNet: New Level of Search Quality. Retrieved 2015-12-24. http://company.yandex.com/technologies/matrixnet.xml ↩
Yandex Boosts Precision Ad Targeting; Machine-Learning Method MatrixNet Is Behind The Scenes. Retrieved 2015-12-24. http://www.dataversity.net/yandex-boosts-precision-ad-targeting-machine-learning-method-matrixnet-is-behind-the-scenes/ ↩
CERN boosts its search for antimatter with Yandex’s MatrixNet search engine tech. Retrieved 2015-12-24. http://www.extremetech.com/extreme/147320-cern-boosts-its-search-for-antimatter-with-yandexs-matrixnet-search-engine-tech ↩