PhD Research Seminar: Time Series Forecasting Based on Automated Machine Learning
Topic: Time Series Forecasting Based on Automated Machine Learning
Speaker: Konstantin Danilov, second-year PhD student, School of Business Informatics
Nowadays, forecasting time series is important in solving a wide range of problems in various spheres of human activity. Researchers resorted to different approaches to achieve the required accuracy of forecasting models, including feature engineering. This presentation will be about a feature engineering method for time series data based on Bayesian optimization. The proposed approach has been experimentally shown to be higly efficient. Some difficulties related to this approach will be discussed.
Гришин Александр Юрьевич
Лаборатория компании Самсунг: Младший научный сотрудник
Данилов Константин Владимирович