Motivation In this paper[1], authors presented a novel group based federated learning to solve incongruent data problem. In traditional FL methods ...
Intuition Authors demonstrated that the gap between centralized and federated performance was caused by two reasons: client drift, a lack of adaptive. Different from variance reduction methods, they e ...
2021-01-22 23:21 0 392 推荐指数:
Motivation In this paper[1], authors presented a novel group based federated learning to solve incongruent data problem. In traditional FL methods ...
A survey on federated learning Authors Chen Zhang, Yu Xie, Hang Bai, Bin Yu, Weihong Li, Yuan Gao Keywords ...
&论文概述 获取地址:https://arxiv.org/abs/1909.06720 &总结与个人观点 本文提出Cascade RPN,虽然简单但是在提高提高候选区域的质量以及目标检测性能上很有效的网络结构。Cascade RPN系统地解决由传统的RPN启发式 ...
目录 摘要 1、引言 2、相关工作 将点云映射到常规二维或三维栅格(体素) 基于MLPs的点表示学习 基于点卷积的点表示学习 动 ...
Visual Object Tracking using Adaptive Correlation Filters 一文发表于2010的CVPR上,是笔者所知的第一篇将correlation filter引入tracking领域内的文章,文中所提的Minimum Output Sum ...
论文笔记:Adaptive Consistency Regularization for Semi-Supervised Transfer Learning Paper: Adaptive Consistency Regularization for Semi-Supervised ...
I. 背景介绍 1. 学习曲线(Learning Curve) 我们都知道在手工调试模型的参数的时候,我们并不会每次都等到模型迭代完后再修改超参数,而是待模型训练了一定的epoch次数后,通过观察 ...
Louvain Introduce Louvain算法是社区发现领域中经典的基于模块度最优化的方法,且是目前市场上最常用的社区发现算法。社区发现旨在发现图结构中存在的类簇(而非传统的向量空间) ...