knowledge and learning
KLLAB News
- Feng Li’s team awarded the Grand Prize for the Tourism Forecasting Competition II
- 2024 PKU Workshop on Modern Bayesian Computation
- A Forecaster’s Review of Judea Pearl’s Causality appeared in International Journal of Forecasting
- Paper “Large Language Models: Their Success and Impact” appeared in Forecasting
- Paper “A hybrid ensemble method with negative correlation learning for regression” appeared in Machine Learning
- We present a modern review on forecast combinations over the past five decades
- Paper “Feature-based intermittent demand forecast combinations: accuracy and inventory implications” appeared in International Journal of Production Research
- New Paper: “Optimal reconciliation with immutable forecasts” appeared in European Journal of Operational Research
- The febama paper is published in the International Journal of Forecasting
- New paper “Escalator accident mechanism analysis and injury prediction approaches in heavy capacity metro rail transit stations” published in Safety Science
Welcome to KLLAB (pronounced as [col·lab], meaning collaborating). A lab for knowledge and learning.
The initiative of KLLAB is to bring collaborations between Prof. Yanfei Kang (Beihang University) and Prof. Feng Li (Peking University)’s students. KLLAB is not only a lab named after Dr. Kang and Li’s initials but also stands for “knowledge and learning” for the people in our lab.
Our KLLAB started as a joint meetup between Beihang University and Central University of Finance and Economics in earlier 2016. In 2020, the KLLAB has reached 20 members.
We focus on finding and solving interesting problems in forecasting, statistical computing, and distributed learning.
Our KLLAB has invited collaborators to visit the lab every year, and we also organize focused workshops with a specific theme. Our research network reaches Australia, UK, Sweden, the US, and other countries. Please checkout our collaboration network on this page.
We welcome university students to join us from all levels, from undergraduates to Ph.D. The KLLAB also sends the best students to the world’s leading universities.
Prof. Yanfei Kang and Prof. Feng Li are also offering undergraduate and graduate-level courses in statistical computing [K][L], Bayesian analysis[K][L], distributed statistical computing [L], and data science [L] every year.