Apr 1, 2024 · We achieve this by incorporating a feedback mechanism into MTL models, where the output of one task serves as a hidden feature for another task, ...
Apr 1, 2024 · We achieve this by incorporating a feedback mechanism into MTL models, where the output of one task serves as a hidden feature for another task, ...
The core message of this paper is to introduce a feedback mechanism into multi-task learning (MTL) models to capture output-level task relatedness, ...
Modeling Output-Level Task Relatedness in Multi-Task Learning with Feedback Mechanism. X. Xi, F. Gao, J. Xu, F. Guo, and T. Jin. CoRR, (2024 ).
To validate our approach on data with different levels of task relatedness, we first apply it to a synthetic dataset where we control the task relatedness.
Missing: Output- Mechanism.
Multi-task learning aims to learn multiple different tasks simultaneously while maximizing performance on one or all of the tasks.
To address this issue, we introduce Selective Sharing, a method that learns the inter-task relatedness from secondary latent features while the model trains.
Missing: Output- | Show results with:Output-
Multi-task learning aims to learn multiple different tasks simultaneously while maximizing performance on one or all of the tasks.
A curated list of datasets, codebases, and papers on Multi-Task Learning (MTL), from a Machine Learning perspective.
论文旨在探索输出级别任务相关性，通过引入反馈机制将多任务学习模型转变为动态模型，提高每个任务的性能。 关键思路.