combinatorial cdeepfuzz learning reading

docker安装msyql5.7报错:mysqld: Can't read dir of '/etc/mysql/conf.d/' (Errcode: 2 - No such file or directory)

安装mysql5.7时使用 #docker拉取镜像命令 docker pull mysql:5.7 #docker安装MySQL命令 docker run -p 3306:3306 --name mysql -v /mydata/mysql/log:/var/log/mysql -v /mydata ......
directory 39 Errcode docker msyql5

【CVPR2023】Learning A Sparse Transformer Network for Effective Image Deraining

论文:https://readpaper.com/paper/4736105248993591297 代码:https://github.com/cschenxiang/DRSformer Transformer 模型通常使用标准的 QKV 三件套进行计算,但是部分来自 K 的 token 与来自 ......

Introduction of Deep Reinforcement Learning

Reading Notes about the book Deep Reinforcement Learning written by Aske Plaat Recently, I have been reading the book Deep Reinforcement Learning writ ......
Reinforcement Introduction Learning Deep of

Tabular Value-Based Reinforcement Learning

Reading Notes about the book Deep Reinforcement Learning written by Aske Plaat Recently, I have been reading the book Deep Reinforcement Learning writ ......

1418 -This function has none of DETERMINISTIC, NO SQL, or READS SQL DATA in its declaration

今天在mysql中创建函数的时候,报错如下: ERROR 1418 (HY000): This function has none of DETERMINISTIC, NO SQL, or READS SQL DATA in its declaration and binary logging is ......
DETERMINISTIC declaration SQL function READS

git clone error: RPC failed; curl 56 OpenSSL SSL_read: SSL_ERROR_SYSCALL, errno 10054

解决方法: git init git config http.postBuffer 524288000 git remote add origin <REPO URL> git pull origin master(主分支) 参考 ......

Paper Reading: WCDForest: a weighted cascade deep forest model toward the classifcation tasks

针对 gcForest 存在的一些缺点,本文提出了一种 WCDForest 模型来提高小样本分类数据集的准确率。为了提高 WCDForest 的特征提取能力,提出了一种等量多粒度扫描模块,可以平等地扫描边缘特征。提出了类向量加权模块和特征增强模块,它们重新评估了 RF 在多粒度扫描和级联森林阶段的分... ......
160 classifcation WCDForest weighted Reading

learn-ue-ui

learn ue ui Created: 2023-10-24T15:29+08:00 Published: 2023-10-25T12:47+08:00 目录IntroWidgetsText Box(Multi-Line) Intro User Interface Development - Un ......
learn-ue-ui learn ue ui

[论文阅读] PCL: Proxy-based Contrastive Learning for Domain Generalization

PCL: Proxy-based Contrastive Learning for Domain Generalization abstract 领域泛化是指从不同源领域的集合中训练模型,该模型可以直接泛化到未见过的目标领域的问题。一种有前途的解决方案是对比学习,它试图通过利用不同领域之间的样本对之 ......

pinia: Cannot read properties of undefined (reading '_s')

使用 Vue3 + Pinia + PNPM + Vite 开发一个前端项目时,运行preview,报错: pinia Cannot read properties of undefined (reading '_s') 报错的代码是压缩后的: function we(e, t, n) { let ......
properties undefined reading Cannot pinia

深度学习调参手册(Deep Learning Tuning Playbook)

google-research/tuning_playbook: A playbook for systematically maximizing the performance of deep learning models. (github.com) dkhonker/tuning_playbo ......
深度 Learning Playbook 手册 Tuning

ST-SSL: 用于交通流量预测的时空自监督学习《Spatio-Temporal Self-Supervised Learning for Traffic Flow Prediction》(交通流量预测、自监督)

2023年10月23日,继续论文,好困,想发疯。 论文:Spatio-Temporal Self-Supervised Learning for Traffic Flow Prediction Github:https://github.com/Echo-Ji/ST-SSL AAAI 2023的论文 ......

Proj CDeepFuzz Paper Reading: POLYCRUISE: A Cross-Language Dynamic Information Flow Analysis

Abstract 本文: PolyCruise Method: 跨编程语言的holistic dynamic information flow analysis(DIFA) use a light language-specific analysis和language-agnostic online ......

Java基础 read (char[] buffer) 底层原理

FileReader fr = new FileReader("E:\\Java基础资料\\a.txt");char[] chars = new char[2];while (true) { int len = fr.read(chars); if (len == -1) break; System ......
底层 原理 基础 buffer Java

Java基础 FileReader——字符输入流之一、read()详解

FileReader:从纯文本文件中读取数据 FileReader 的使用步骤: 1. 创建字符输入流对象 → public FileReader (File file) 或者 public FileReader (String pathname) 细节:如果文件不存在,就直接报错 2. 读取数据 ......
FileReader 字符 基础 Java read

[论文速览] SimCSE@ Simple Contrastive Learning of Sentence Embeddings

Pre title: SimCSE: Simple Contrastive Learning of Sentence Embeddings accepted: EMNLP 2021 paper: https://arxiv.org/abs/2104.08821 code: https://githu ......

Scikit-learn 的 preprocessing.LabelEncoder函数:标签编码

参考文档:https://pythonjishu.com/sklearn-preprocessing-labelencoder/ 转换类别数据为整数:LabelEncoder 可以将字符串或其他类别型数据转换为整数。例如,如果你有一个特征包含类别 "红色"、"绿色" 和 "蓝色",LabelEnco ......

docker exec 报错 decoding init error from pipe caused \"read parent: connection reset by peer\""

复现方法,限制容器内pid个数 docker run --pids-limit=1000 -d centos sleep 100000 docker exec -it id bash 3.执行 for i in $(seq 1 2000); do (sleep 100&) ; done [root@ ......
quot connection decoding docker caused

Paper Reading: Sample and feature selecting based ensemble learning for imbalanced problems

为了克服现有集成方法的缺点,本文提出一种新的混合集成策略——样本和特征选择混合集成学习 SFSHEL。SFSHEL 考虑基于聚类的分层对大多数样本进行欠采样,并采用滑动窗口机制同时生成多样性的特征子集。然后将经过验证训练的权重分配给不同的基学习器,最后 SFSHEL 通过加权投票进行预测。SFSHE... ......

强化学习Q-Learning和DQN算法

1 Q-Learning 强化学习中有state和action的两个重要概念。而Q-Learning算法就是用来得到在state上执行action的未来预期奖励。具体的算法流程如下: 初始化一个Q-table。 在当前状态\(s\)选择一个动作\(a\)。 执行动作\(a\),转移到新的状态\(s' ......
算法 Q-Learning Learning DQN

不修改Read/Write Enabled,Texture.GetPixels,Mesh.triangles

### 原理:将Texture拷贝一份出来然后读取 /// <summary> /// 不通过设置Read/Write Enabled,直接克隆一份可读的Texture2D /// </summary> /// <param name="source"></param> /// <returns>< ......
GetPixels triangles Enabled Texture Write

Learn Git in 30 days—— 第 30 天:分享工作中几个好用的 Git 操作技巧

写的非常好的一个Git系列文章,强烈推荐 原文链接:https://github.com/doggy8088/Learn-Git-in-30-days/tree/master/zh-cn 终于来到了最后一天,这篇文章将分享几个好用的 Git 操作技巧,或许可以节省你不少 Git 版控过程的时间。 如 ......
Git 技巧 Learn 30 days

vue进行跳转之后出现Cannot read properties of undefined (reading 'router') TypeError: Cannot read properties of undefined (reading 'router'的问题

问题描述 使用router进行页面跳转时,就出现了这样的问题: 也就是这里出现了问题: 问题解决 本来是按照网上的教程: const _this=this; 但是,但是,我本来就是用的这种方法呀~ 然后就打算直接在这个界面引用: import router from '@/router' route ......
properties undefined reading Cannot router

Robust Graph Representation Learning via Neural Sparsification

目录概符号说明NeuralSparse Zheng C., Zong B., Cheng W., Song D., Ni J., Yu W., Chen H. and Wang W. Robust graph representation learning via neural sparsifica ......

论文阅读 Generalized Focal Loss: Learning Qualified and Distributed Bounding Boxes for Dense Object Detection

原始题目:Generalized Focal Loss: Learning Qualified and Distributed Bounding Boxes for Dense Object Detection 中文翻译:Generalized Focal Loss:学习用于密集目标检测的 Qual ......

[911] Read Data from Google Sheets into Pandas without the Google Sheets API (.gsheet)

ref: Read Data from Google Sheets into Pandas without the Google Sheets API import pandas as pd sheet_id = "1XqOtPkiE_Q0dfGSoyxrH730RkwrTczcRbDeJJpqRB ......
Google Sheets without Pandas gsheet

Meta Learning概述

Meta Learning概述(一) 回顾Machine Learning 定义一个function(神经网络等),该function上有很多参数,参数统一定义为θ,对于一个猫狗分类器来说,当猫狗的图片经过f(θ)时,函数会输出一个猫或狗的结果 定义一个Loss function,L(θ) 使用优化 ......
Learning Meta

Paper Reading: Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold

为了实现基于 GAN 的交互式的基于点的操作,本文提出了 DragGAN,它解决了监督手柄点向目标移动和跟踪手柄点两个子问题,以便在每个编辑步骤中知道它们的位置。本文模型是建立在 GAN 的特征空间具有足够的区分力以实现运动监督和精确点跟踪的特性之上的,运动监督通过优化潜在代码的移位特征损失来实现的... ......

《Deep Residual Learning for Image Recognition》阅读笔记

论文标题 《Deep Residual Learning for Image Recognition》 撑起CV界半边天的论文 Residual :主要思想,残差。 作者 何恺明,超级大佬。微软亚研院属实是人才辈出的地方。 初读 摘要 提问题: 更深层次的神经网络更难训练。 提方案: 提出了残差网络 ......
Recognition Residual Learning 笔记 Image

Sequence to Sequence Learning with Neural Networks

Sequence to Sequence Learning with Neural Networks 关键词:LSTM,Seq2Seq 📜 研究主题 采用深度神经网络DNN 使用LSTM,并翻转输入句子顺序提升性能 ✨创新点: 更换seq2seq中RNN单元为LSTM,有提升对长句子训练速度的可能 ......
Sequence Learning Networks Neural with