多任务学习是继深度学习能够解决单个分类或回归问题之后的一个重要研究方向,它提出的主要背景是,算法工程师总能希望进行一次训练,可以将多个相关的任务目标或不那么相关的目标进行统一的学习,想法很容易理解,这样Multi Task Learing既可以找到同一个对象的多个任务(诸如一个人的身高、体重、年龄、收入等多个目标的预测)相关联系,以便于更好
Multi-domain multi-task learning Rebuffi, S.-A., Bilen, H., & Vedaldi, A.Learning multiple visual domains with residual adapters. NeurIPS, 2017. BDD100K [URL] 10-task Driving Dataset Yu, F., Chen, H., Wang, X., Xian, W., Chen, Y., Liu, F., Madhavan, V., & Darrell, T....
开源实现:github.com/chainer/mode 原理解析:常见多任务学习关注与前向过程,但实际影响结果的是反向过程的梯度分配 改进点:每个任务每一次反向梯度给与一个权重W,调整梯度的量值 In general, multitask networks are difficult to train; different tasks need to be properly balanced so network parameters converge...
Multi-Task Learning: GradNorm 论文链接: 开源实现:https://github.com/chainer/models/tree/master/grad-norm原理解析:常见多任务学习关注与前向过程,但实际影响结果的是反向过程的梯度分配改进点:每个任务每一次反向梯度给与一个权重W,调整梯度的量值In general, multitask networks are difficult to train… ...
Multi-Task Learning in Tensorflow (Part 1) blog:https://jg8610.github.io/Multi-Task/ Deep Multi-Task Learning with Shared Memory intro: EMNLP 2016 arxiv:http://arxiv.org/abs/1609.07222 Learning to Push by Grasping: Using multiple tasks for effective learning ...
Fig. 1: Multi-task learning of multi-modality biological data by UnitedNet. a Schematics of representative multi-modality biological data: (i) simultaneously measured transcriptomics and intracellular electrophysiology (multi-sensing data), (ii) integratively profiled transcriptomics and DNA accessibility ...
Code:https://github.com/facebookresearch/vilbert-multi-task 1. Background and Motivation: 本文提出了一种多任务学习的方法,可以将不同 vision-language 任务放到一个模型中进行训练。得到了更好的性能提升,所有任务的平均提升幅度为 2.05 个点。之所以这么做,是因为虽然 vision-language 任务设定不同,但是均需...
oSFU Machine Learning Reading Group Github代码 oLogistic Regression Multi-task logistic regression in brain-computer interfaces oBayesian Methods Kernelized Bayesian Multitask Learning Parametric Bayesian multi-task learning for modeling biomarker trajectories ...
Without incorporating task-specific prior knowledge and highly specialized network designs, our approach achieves state-of-the-art results on three different multi-attribute learning tasks, compared to highly customized domain-specific methods. Code is available at https://github.com/Li-Wanhua/Label2...
论文地址:https://www.kdd.org/kdd2018/accepted-papers/view/modeling-task-relationships-in-multi-task-learning-with-multi-gate-mixture- 非官方代码:https://github.com/drawbridge/keras-mmoe 一 为什么读这篇 动机是做粗排模型看能不能参考精排的MMoE模型,也经常听到同组的同学在讨论这个模型,算是解决多...