JointNet: Multitask Learning Framework for Denoising and Detecting Anomalies in Hyperspectral Remote Sensingdoi:10.3390/rs16142619IMAGE denoisingREMOTE sensingDATA integrityNOISEINFORMATION sharingOne of the significant challenges with traditional single-task learning-based anomaly detection using noisy ...
A multi-task learning (MTL) framework. It shares the same encoder across multiple decoders. These decoders can have dependencies on each other which will be properly handled during decoding. To integrate a component into this MTL framework, a component needs to implement the Task interface....
XDL: An Industrial Deep Learning Framework for High-dimensional Sparse Data 论文笔记 本文的github地址: https://github.com/alibaba/x-deeplearning X-Deep Learning(简称XDL)于2018年12月由阿里巴巴开源,是面向高维稀疏数据场景(如广告/推荐/搜索等)深度优化的一整套解决方案。以填补 TensorFlow、PyTorch 等...
与Multitask Learning相对的就是Single-task Learning, Single-task Learning就是之前的一个model解决某个任务的模型. 而从CV pre-train model的预训练模型得到启发, NLP当然也可以用预训练模型. 那么我们想要的其实就是一个unified multi-task model, 想到了之前看的一篇sentiment analysis论文[3], 把情感分析用一...
We propose a novel cyclic multitask learning framework for neural simile recognition, which stacks the subtasks and makes them into a loop by connecting the last to the first.It iteratively performs each subtask,taking the outputs of the previous subtask as additional inputs to the current ...
our new 3D real-time augmentation algorithm (Shift3D) introduces space variances for 3D CNN components by shifting low-level feature representations of volumetric inputs in three dimensions; thereby, the MTL framework is able to accelerate convergence and improve joint learning performance compared to ...
This paper presents a new multitask learning framework that learns a shared representation among the tasks, incorporating both task and feature clusters. The jointly-induced clusters yield a shared latent subspace where task relationships are learned more effectively and more generally than in state-of...
By improving the attention mechanism, the emotional contribution of each modality is further analyzed so that the emotional representations of each modality can learn from and complement each other to achieve better interactive fusion effect, thereby building a multitask learning framework. By introducing...
Awesome Multitask Learning Resources. Contribute to mbs0221/Multitask-Learning development by creating an account on GitHub.
Using the multitask learning framework, we successfully identify 18 common features shared by four kinase families of phosphorylation sites. The reliability of selected features is demonstrated by the consistent performance in two multi-task learning methods. Conclusions The selected features can be used...