The FFORMPP paper is accepted in the International Journal of Forecasting Thiyanga S. Talagala, Feng Li, Yanfei Kang (2021). FFORMPP: Feature-based forecast model performance prediction. International Journal of Forecasting. (in press) [ arXiv | R package ] This paper introduces a novel meta-learning algorithm for time series forecast model performance prediction. We model the forecast error as a function of time series features […]
Author: Feng Li
Dr. Feng Li is an Associate Professor of Statistics in the School of Statistics and Mathematics at Central University of Finance and Economics in Beijing, China. Feng obtained his Ph.D. degree in Statistics from Stockholm University, Sweden in 2013. His research interests include Bayesian computation, econometrics and forecasting, and distributed learning. His recent research output appeared in statistics and forecasting journals such as the International Journal of Forecasting and Statistical Analysis and Data Mining, AI journals such as Expert Systems with Applications, and medical journals such as BMJ Open.
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Meet our KLLAB members on ISF 2021
Our KLLAB members will be presenting our work at the invited session of the 41st International Symposium on Forecasting virtually. ECR – Visibility Panel Time: Mon. Jun 28, 2021 11:00 AM – 12:00 PM (UTC+8) https://whova.com/portal/webapp/iiofe_202106/Agenda/1753058 Chaired by Shari De Baets In a world ruled by the internet and social media, it is more important than ever […]
Dr. Feng Li will be presenting at the 2021 world meeting of the International Society for Bayesian Analysis (ISBA) on session of C28: Bayesian Inference and Forecasting for Business Problems. Time: Friday, July 2, 6:45 am – 8:00 am Whova Link: https://whova.com/embedded/session/isbaw_202106/1572928/ Meeting Program: https://events.stat.uconn.edu/ISBA2021/programs.html The International Society for Bayesian Analysis (ISBA) was founded in 1992to promote the development and application of Bayesian analysis. By sponsoring […]
Authors: Xuening Zhu, Feng Li and Hansheng Wang Abstract: In this work we develop a distributed least squares approximation (DLSA) method, which is able to solve a large family of regression problems (e.g., linear regression, logistic regression, Cox’s model) on a distributed system. By approximating the local objective function using a local quadratic form, we are able to obtain a […]
Authors: Yanfei Kang, Wei Cao, Fotios Petropoulos, Feng Li Abstract: Forecast combination has been widely applied in the last few decades to improve forecast accuracy. In recent years, the idea of using time series features to construct forecast combination model has flourished in the forecasting area. Although this idea has been proved to be beneficial in […]
Our lab members will be presenting our work at the invited session of the 40th International Symposium on Forecasting virtually. Session: Forecast Combination Time: October 26, Monday, 17:00-18:00 GMT+8 Detailed Schedule: https://whova.com/embedded/session/iiofe_202006/1323449/ Speakers Yanfei Kang (Speaker) Associate Professor, School of Economics and Management, Beihang University Xiaoqian Wang (Speaker) PhD student, Beihang University Xixi Li (Speaker) […]
Our foresting paper with time series imaging approach is accepted in Expert Systems with Applications. Xixi Li, Yanfei Kang, and Feng Li*. (2020). Forecasting with time series imaging, Expert Systems with Applications. (In Press) [Working Paper | Software] Feature-based time series representations have attracted substantial attention in a wide range of time series analysis methods. Recently, the use of […]
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We have a lab now!
We are so excited to announce that Yanfei and Feng’s group now has an official lab, named KLLAB (pronounced as [col·lab], meaning collaborating) and a website KLLAB.org. Have fun!