MUMBAI, India, Sept. 5 -- Intellectual Property India has published a patent application (202421015031 A) filed by Tata Consultancy Services Limited, Maharashtra, on Feb. 29, 2024, for 'systems and methods for optimizing hyperparameters of machine learning models using reduction iteration techniques.'
Inventor(s) include Ling, Yibei; and Njelita, Charles.
The application for the patent was published on Sept. 5, under issue no. 36/2025.
According to the abstract released by the Intellectual Property India: "The most fundamental task in ML models is to automate the setting of hyperparameters to optimize performance. Traditionally, in machine learning (ML) models hyperparameter optimization problem has been solved using brute-force techniques such as grid search, and the like. This strategy exponentially increases computation costs and memory overhead. Considering the complexity and variety of the ML models there still remains practical difficulties of selecting right combinations of hyperparameters to maximize performance of the ML models. Embodiments of the present disclosure provide systems and methods for hyperparameters optimization in machine learning models and to effectively reduce the hyperparameter search dimensions and identify the important hyperparameter dimensions that are high variable to identify the best hyperparameter thereby saving the computing energy of machine learning process and eliminate categorical dimensions by using a combination of reduction-iteration techniques."
Disclaimer: Curated by HT Syndication.
