Jan 22, 2021 · We introduce the novel cluster layer, which groups tasks into clusters during training procedures. In a cluster layer, the tasks in the same cluster are ...
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This paper uses the multi-task learning framework to jointly learn across multiple related tasks based on recurrent neural network.
In a cluster layer, the tasks in the same cluster are further required to share the same network. By this way, the cluster layer produces the general ...
Network Clustering for Multi-task Learning - ResearchGate
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ABSTRACT. The Multi-Task Learning (MTL) technique has been widely studied by word-wide researchers. The majority of current MTL.
May 16, 2023 · This article focuses on clustered multi-task learning, where agents are partitioned into clusters with distinct objectives, and agents in the ...
This model adopts a multi-task learning framework, enhanced with time-series clustering for nuanced pattern recognition and improved prediction accuracy in ...
Jan 30, 2024 · This work introduces a methodology, termed MTEFU, leveraging a deep learning model-based multi-task learning algorithm, strategically designed to mitigate the ...
Jan 13, 2020 · In this paper, we propose a novel method, Multi-Task Learning-Based Network Embedding, termed MLNE. There are two tasks in this method so as to preserve the ...
Abstract. Modeling a collection of similar regression or classification tasks can be improved by making the tasks 'learn from each other'.
In this paper, we propose a multi-task clustering with model rela- tion learning (MTCMRL) method, which automat- ically learns the model parameter relatedness ...