写在前面:多数关于多任务学习(Multi-task learning)的文章、综述或者paper都聚焦于网络结构的迭代与创新;然而,对于多任务学习Loss的优化也非常重要。本文基于多任务学习在2020年的一篇综述——《Multi-Task Learning for Dense Prediction Tasks: A Survey》中的部分内容,尽量用通俗易懂的方式来聊聊多任务学习优化的问题。
[论文翻译]Multi-Task Learning for Dense Prediction Tasks: A Survey,程序员大本营,技术文章内容聚合第一站。
Multi-Task Learning as Multi-Objective Optimization https://zhuanlan.zhihu.com/p/68846373 GradNorm: Gradient Normalization for Adaptive Loss Balancing in Deep Multitask Networks Multi-Task Learning for Dense Prediction Tasks:A Survey Modeling Task Relationships in Multi-task Learning with Multi-gate Mixt...
The resultant map identifying one or more points corresponding to the one or more features. The computing system may provide the one or more points identified in the resultant map for the biomedical image.Chensu Xie
With the advent of deep learning, many dense prediction tasks, i.e. tasks that produce pixel-level predictions, have seen significant performance improvements. The typical approach is to learn these tasks in isolation, that is, a separate neural network is trained for each individual task. Yet,...
resnet_v2.preprocess_input)(x) x = base_model(x) x = Dropout(0.5)(x) x = [Dense(...
深度学习算法中的多任务学习(Multi-task Learning) 引言 深度学习算法在各个领域取得了巨大的成功,但在大多数情况下,我们只关注单个任务的解决方案。然而,在现实世界中,往往存在多个相关任务需要同时解决。多任务学习(Multi-task Learning)就是一种能够同时学习多个相关任务的深度学习方法,它可以通过共享模型参数来提高整...
Multi-Task Learning This repo aims to implement several multi-task learning models and training strategies in PyTorch. The code base complements the following works: Multi-Task Learning for Dense Prediction Tasks: A Survey Simon Vandenhende,Stamatios Georgoulis, Wouter Van Gansbeke, Marc Proesmans...
✨ Vandenhende, S., Georgoulis, S., Proesmans, M., Dai, D., & Van Gool, L.Multi-Task Learning for Dense Prediction Tasks: A Survey. TPAMI, 2021. Crawshaw, M.Multi-Task Learning with Deep Neural Networks: A Survey. ArXiv, 2020. ...
· Multi-Task Learning for Dense Prediction Tasks: A Survey 另外,杨强教授还有一篇综述 《A Survey on Transfer Learning》,里面也有不少多任务学习和迁移学习的对比思考,本来这两个领域就很有相通之处,容易被联系起来,尤其是在learning technique层面,跳出来看,很多知识都是一脉相承。