1 code implementation • 21 Mar 2020 • Changming Zhao, Dongrui Wu, Jian Huang, Ye Yuan, Hai-Tao Zhang, Ruimin Peng, Zhenhua Shi
Bootstrap aggregating (Bagging) and boosting are two popular ensemble learning approaches, which combine multiple base learners to generate a composite model for more accurate and more reliable performance.
1 code implementation • 3 Jul 2020 • Dongrui Wu, Xue Jiang, Ruimin Peng, Wanzeng Kong, Jian Huang, Zhigang Zeng
Transfer learning (TL) has been widely used in motor imagery (MI) based brain-computer interfaces (BCIs) to reduce the calibration effort for a new subject, and demonstrated promising performance.