Jan 31, 2018 · The MDOS-ELM successfully addresses two problems of online learning. The first one is the timeliness of the training samples and the second is ...
Jan 31, 2018 · In online learning, the contribution of old samples to a model decreases as time passes, and old samples gradually become invalid. Although the ...
Although the Online Sequential Extreme Learning Machine (OS-ELM) can avoid the repetitive training of old samples, invalid samples are still used, which goes ...
This work reviews the most important and latest works in OS-ELM family and consists of two topics, one related to the improved version of OS-elM which aims ...
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Jan 24, 2024 · 周昌军,英文主页The memory degradation based online sequential extreme learning machine,浙江师范大学教师个人主页系统,周昌军，浙江师范大学数学 ...
This paper has developed a novel updating strategy for setting the forgetting factor and proposed a dynamic forgetting factor based OS-ELM algorithm, ...
In this paper, the online sequential extreme learning machine (OS-ELM)-based method, which is dedicated to high-efficiency active interference activity ...
Jun 7, 2022 · In this paper, the online sequential extreme learning machine (OS-ELM)-based method, which is dedicated to high-efficiency active interference activity ...
Dec 18, 2019 · With this in mind, this paper proposes a novel robust adaptive online sequential extreme learning machine (RA-OSELM) algorithm for the online ...
Dec 23, 2019 · ABSTRACT Online sequential extreme learning machine (OS-ELM) and its variants provide a promising way to solve data stream problems, ...