Jun 24, 2021 · In this article, we propose a novel OTL framework for a regression task, which includes an offline stage and an online stage.

Jun 26, 2021 · Online transfer learning (OTL), as one type of transfer learning, deals with the situation where the data of target domain arrive in a ...

The effectiveness of the proposed framework is verified by a real dataset regarding the diesel hydrofining process collected from a petrochemical workshop.

This paper proposes novel online transfer learning paradigms in which the source and target domains are leveraged adaptively and works in an online manner, ...

This paper proposes a combinational transfer learning framework to update transient stability prediction model in time-varying power systems.

Recently, many excellent algorithms for time series prediction issues have been proposed, most of which are developed based on the assumption that ...

This paper investigates a new machine learning framework called Online Transfer Learning (OTL) that aims to transfer knowledge from some source domain to an ...

In this paper, we investigate a new machine learning framework called Online Transfer. Learning (OTL) that aims to transfer knowl- edge from some source domain ...

In this paper, we propose a novel machine learning framework called “Online Transfer Learning” (OTL), which aims to attack an online learning task on a target ...

However, time series data always produces some time-varying characteristics over time, which will lead to relatively large differences between old and new data.