teaching machine overview of
CF1912J Joy of Pokémon Observation记录
题目链接:https://codeforces.com/contest/1912/attachments/download/23419/icpc-nerc-2023-statements.pdf 题意简述 求方程 \(\sum \limits_{i =1}^{s} l_i x_i = t\) 的非负 ......
Nacos启动:[NACOS HTTP-POST] The maximum number of tolerable server reconnection errors has been reached
一、表象 二、分析 源码: public HttpRestResult<String> httpPost(String path, Map<String, String> headers, Map<String, String> paramValues, String encode, long re ......
Feedback Control of Dynamic Systems_P2
187. Problems for Section 5.4: Design Using Dynamic Compensation 5.21 Let \[G(s) = \frac{1}{s^{2} + 7s + 12}\ \text{~}\text{and}\text{~}\ D_{c}(s) = K ......
Feedback Control of Dynamic Systems_P1
GLOBAL EDITION 1. Feedback Control of Dynamic Systems EIGHTH EDITION Franklin \(\cdot\) Powell \(・\) Emami-Naeini Table of Laplace Transforms Number \ ......
[ARC107F] Sum of Abs
[ARC107F] Sum of Abs 发现点数比较少,考虑最小割 我们最大可能的答案为 \(\sum|b_i|\) ,现在考虑减去多余答案 首先点可以不选,于是拆点,之间边权为 \(a_i+|b_i|\) 钦定割完之后,和 \(S\) 连通的点最终取正数,和 \(T\) 连通的点最终取负数,于是 ......
IDEA中出现java file outside of source root
该问题出现原因是,该文件不可编译,需要设置一下sourcesRoot, 一般设置java文件夹为sourceRoot,否则原来的package路径需要更改 ......
Sum of XOR Functions 题解
题意 给定一个数 \(n\) 和一个包含 \(n\) 个数的序列 \(a\),求出以下式子模 \(998244353\) 的值: \(\sum_{i=1}^{n}\sum_{j=i}^{n} f(i,j)\times (j-i+1)\)。 其中 \(f(i,j)\) 的值为 \(a_{i}\oplu ......
Nacos启动:[NACOS HTTP-POST] The maximum number of tolerable server reconnection errors has been reached
一、表象 二、分析 源码: public HttpRestResult<String> httpPost(String path, Map<String, String> headers, Map<String, String> paramValues, String encode, long re ......
Bias of an estimator
Bias of an estimator Difference between an estimator's expected value from a parameter's true value For broader coverage of this topic, see Bias (stat ......
BigdataAIML-ML-Models for machine learning Explore the ideas behind machine learning models and some key algorithms used for each
最好的机器学习教程系列:https://developer.ibm.com/articles/cc-models-machine-learning/ By M. Tim Jones, Published December 4, 2017 Models for machine learning Alg ......
CARAFE: Content-Aware ReAssembly of FEatures 可学习的上采样
CARAFE: Content-Aware ReAssembly of FEatures * Authors: [[Jiaqi Wang]], [[Kai Chen]], [[Rui Xu]], [[Ziwei Liu]], [[Chen Change Loy]], [[Dahua Lin]] DO ......
UNetFormer: A UNet-like transformer for efficient semantic segmentation of remote sensing urban scene imagery
UNetFormer: A UNet-like transformer for efficient semantic segmentation of remote sensing urban scene imagery * Authors: [[Libo Wang]], [[Rui Li]], [[ ......
用DE10_NANO_SOC_FB生成dts的时候 提示Component alt_vip_itc_0 of class alt_vip_itc is unknown
当使用DE10_NANO_SOC_FB工程产生dts时提示 Component alt_vip_itc_0 of class alt_vip_itc is unknown: 如果此时生成了dtb, 可以忽略这个提示。 如果没有生成,您可以先在Qsys 中把这两个器件disable 掉, 然后top文 ......
A Guide to Image and Video based Small Object Detection using Deep Learning : Case Study of Maritime Surveillance
A Guide to Image and Video based Small Object Detection using Deep Learning : Case Study of Maritime Surveillance 基于图像和视频的小对象指南使用深度学习进行检测:的案例研究海上监视 1 ......
神经网络优化篇:机器学习基础(Basic Recipe for Machine Learning)
机器学习基础 下图就是在训练神经网络用到的基本方法:(尝试这些方法,可能有用,可能没用) 这是在训练神经网络时用到地基本方法,初始模型训练完成后,首先要知道算法的偏差高不高,如果偏差较高,试着评估训练集或训练数据的性能。如果偏差的确很高,甚至无法拟合训练集,那么要做的就是选择一个新的网络,比如含有更 ......
Machine Learning in Python
Metric Formula Interpretation Accuracy $ \frac{TP+TN}{TP+TN+FP+FN} $ Overall performance of model Precision $ \frac{TP}{TP+FN} $ How accurate the posi ......
POLIR-Management-TYPES of decisions
In a very simple sense, the problems managers encounter can be classified as: routine and familiar; new and unusual. In response, managers will use on ......
一句话解决加载模型时的CUDA out of memory
在加载模型一行后加上max_memory即可,超出显存后会自动移到内存。 model = AutoModel.from_pretrained('your_model', trust_remote_code=True, max_memory={0: "6GiB", "cpu": "10GiB"}) 记 ......
[LeetCode] 2415. Reverse Odd Levels of Binary Tree
Given the root of a perfect binary tree, reverse the node values at each odd level of the tree. For example, suppose the node values at level 3 are [2 ......
Failed to convert property value of type 'java.lang.String' to required type 'java.util.Date' for property 'endTime';
后端springboot项目使用getMapper接受,字段写了转换注解 @JsonFormat(shape = JsonFormat.Shape.STRING, pattern = "yyyy-MM-dd HH:mm:ss", timezone = "GMT+8") 还报错Failed to co ......
[ARC124C] LCM of GCDs 题解
题目跳转 Fake_Solution 前言 [warning]: 本题解的做法是错法,但是正确概率贼高。离谱的是正确率还可以叠加。 正解是记搜,时间复杂度可以证明。正解看文末。 思考 众所周知一个公式: \[a\times b=\operatorname{lcm}(a,b)\times \gcd(a ......
React报错:Warning: Invalid hook call. Hooks can only called inside of the body of a function component. This could happen for one of the following reasons: .......
报错截图: 问题可能原因: 我之前是用 npm install,后面有些依赖用的是 cnpm install 解决方法: 用统一的安装方式 删除 node_modules,重新执行 cnpm install 我这里解决问题 ......
Java: OpenWeatherMap json Deserialization of Java Objects
openweathermap.json { "coord": { "lon": 114.0683, "lat":22.5455 } , "weather":[ { "id": 803, "main":"Clouds", "description":"多云", "icon":"04d" } ], "b ......
《Progressive Learning of Category-Consistent Multi-Granularity Features for Fine-Grained Visual Classification》阅读笔记
论文标题 《Progressive Learning of Category-Consistent Multi-Granularity Features for Fine-Grained Visual Classification》 细粒度视觉分类中类别一致多粒度特征的渐进学习 作者 Ruoyi D ......
Python: json Deserialization of Python Objects
openweathermap.json { "coord": { "lon": 114.0683, "lat":22.5455 } , "weather":[ { "id": 803, "main":"Clouds", "description":"多云", "icon":"04d" } ], "b ......
js (for in)和(for of)区别
for...in 语句以任意顺序迭代一个对象的除Symbol以外的可枚举属性,包括继承的可枚举属性。 for...of语句在可迭代对象(包括 Array,Map,Set,String,TypedArray,arguments 对象等等)上创建一个迭代循环,调用自定义迭代钩子,并为每个不同属性的值执行 ......
使用Apache POI 导入导出时出现You need to call a different part of POI to process this data (eg XSSF instead of HSSF)Java异常
问题复现 在学习导出功能时使用HSSFWorkbook导出了一个xxx.xlsx格式的文件,然后用XSSFWorkbook的读取方式来拿文件去导入时出现了这个bug 这是当时做导出测试代码 Workbook wb = new HSSFWorkbook(); CreationHelper creati ......
Machine is not on the network
在调试Android jni 的时候发现一个奇怪的问题 在连接socket的时候老是报错 m_sock = socket(AF_INET, SOCK_STREAM, 0); if(m_sock < 0) { debug(LEVEL_ERROR, "Socket create error %d\r\n ......
【Linux API 揭秘】container_of函数详解
1、container_of函数介绍
container_of可以说是内核中使用最为频繁的一个函数了,简单来说,它的主要作用就是根据我们结构体中的已知的成员变量的地址,来寻求该结构体的首地址,直接看图,更容易理解。 ......