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 ...
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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 ...
&論文概述 獲取地址:https://arxiv.org/abs/1909.06720 &總結與個人觀點 本文提出Cascade RPN,雖然簡單但是在提高提高候選區域的質量以及目標檢測性能上很有效的網絡結構。Cascade RPN系統地解決由傳統的RPN啟發式 ...
目錄 摘要 1、引言 2、相關工作 將點雲映射到常規二維或三維柵格(體素) 基於MLPs的點表示學習 基於點卷積的點表示學習 動 ...
Visual Object Tracking using Adaptive Correlation Filters 一文發表於2010的CVPR上,是筆者所知的第一篇將correlation filter引入tracking領域內的文章,文中所提的Minimum Output Sum ...
論文筆記:Adaptive Consistency Regularization for Semi-Supervised Transfer Learning Paper: Adaptive Consistency Regularization for Semi-Supervised ...
I. 背景介紹 1. 學習曲線(Learning Curve) 我們都知道在手工調試模型的參數的時候,我們並不會每次都等到模型迭代完后再修改超參數,而是待模型訓練了一定的epoch次數后,通過觀察 ...
Louvain Introduce Louvain算法是社區發現領域中經典的基於模塊度最優化的方法,且是目前市場上最常用的社區發現算法。社區發現旨在發現圖結構中存在的類簇(而非傳統的向量空間) ...