In this paper, we propose a Robust Multi- Task Feature Learning algorithm (rMTFL) which simultaneously captures a common set of features among relevant tasks and identifies outlier tasks. Specifically, we decompose the weight (model) matrix for all tasks into two components. We impose the well-...
Multi-task learning (MTL) considers learning a joint model for multiple tasks by optimizing a convex combination of all task losses. To solve the optimization problem, existing methods use an adaptive weight updating scheme, where task weights are dynamically adjusted based on their respective losses...
Adaptive and Robust Multi-Task Learning 上传人:leo_wyoming · 上传时间:2024-11-08 1/7298% 0% 0% 0%0%继续阅读 VIP精选文档 11 2009年高考陕西文科数学卷解析 7 机械社区关于步进电机的讨论 9 安信证券-估值与盈利监测周报-091227 6 江苏省海门中学2008-2009学年度第二学期期中考试试卷 VIP文档折扣下载...
Robust Multi-Task Learning and Online Refinement for Spacecraft Pose Estimation across Domain Gap 来自 arXiv.org 喜欢 0 阅读量: 130 作者:TH Park,S D'Amico 摘要: This work presents Spacecraft Pose Network v2 (SPNv2), a Convolutional Neural Network (CNN) for pose estimation of noncooperative ...
中Distral是Distill &transferlearning的缩写。 原文传送门 Teh, Yee, et al. "Distral: Robust multitask reinforcement learning." Advances in Neural Information Processing Systems. 2017. 特色 提出了一种同时在多个任务上训练的强化学习方法,主要的想法是把各个任务上学到的策略进行提纯(distill,本意是蒸馏)得到...
原来的题目Federated Multi-Task Learning for Competing Constraints 关于作者 这篇论文的作者在17年就挖了“联邦多任务学习”这个坑,在这四年里一直在做关于这方面的内容,感觉值得学习。不能不停挖新坑,应该找对一个坑深挖。 摘要 首先介绍一下联邦学习中公平性和鲁棒性的定义。
To handle possible misspecification of the structure, we propose a method named Adaptive and Robust MUlti-Task Learning (ARMUL):min Θ ∈ R d × m , Γ ∈ Ω { ∑ j = 1 m w j [ f j ( θ j ) + λ j ‖ θ j − γ j ‖ 2 ] } ....
aware Network (MPN), which is designed to extract semantically aligned part-level features from pedestrian images. MPN solvesthe body part misalignment problem via multi-task learning (MTL) in the training stage. More specif i cally, it builds one main task (MT)and one auxiliary task (AT) ...
与常见的multi-task RL的设计不同,一般来说是给每一个任务赋予一个one-hot编码,然后为神经网络设计一个task encoder,用来将one-hot编码映射为一个连续空间表征向量e。但是在TD-MPC2中,e是一个神经网络参数,在训练过程中通过梯度下降和其他所有模型一同完成训练,但他被限制为二范数小于等于1(位于一个高维球内),...
An Overview of Multi-Task Learning in Deep Neural Networks Multi-task learning (MTL) has led to successes in many applications of machine learning, from natural language processing and speech recognition to compute... S Ruder 被引量: 176发表: 2017年 Deep Neural Networks for Single-Channel ...