526互联

dbc-forest confidence screening reading

window.screen对象

Screen 接口表示一个屏幕窗口，往往指的是当前正在被渲染的 window 对象，可以使用 window.screen 获取它。 属性 属性 描述 availTop 返回不包含用户界面的第一个y坐标像素值 availLeft 返回屏幕左边边界的第一个像素点 availHeight 返回不包含任务栏 ......
对象 window screen

Screen fragments should never be restored. Follow instructions from https://github.com/software-mansion/react-native-screens/issues/17#issuecomment-424704067 to properly configure your main activity.

Screen fragments should never be restored. Follow instructions from https://github.com/software-mansion/react-native-screens/issues/17#issuecomment-42... ......
react-native-screens software-mansion instructions issuecomment 424704067

Proj. CRR Paper Reading: Optimal Speedup of Las Vegas Algorithms, Adaptive restart for stochastic synthesis

Title Adaptive restart for stochastic synthesis PLDI 2021 Task Distribute the power between multiple runs in stochastic program synthesis to accelerat ......
Algorithms stochastic synthesis Adaptive Optimal

Paper Reading: Hashing-Based Undersampling Ensemble for Imbalanced Pattern Classification Problems

针对欠采样方法会丢弃大量多数类样本导致信息缺失的问题，本文提出了基于哈希的欠采样集成 HUE 模型，它利用 Bagging 和多数类样本的分布特征来构建多样化的训练子集。首先 HUE 通过散列将大多数类样本划分为不同的特征子空间，然后使用所有少数样本和主要从同一哈希子空间中提取的部分多数样本来构建训... ......
Classification Hashing-Based Undersampling Imbalanced Ensemble

Seeing What You Said: Talking Face Generation Guided by a Lip Reading Expert 论文笔记

最近一直在看虚拟人像. 最关键的论文就是wav2lip. 目前项目中也是用的这个. 一个视频加一个语音, 就可以生成用视频里面的头,加语音的新视频. 现在看这篇论文Seeing What You Said: Talking Face Generation Guided by a Lip Readin ......
Generation Reading Talking 笔记 Seeing

What We’re Reading: What makes you happy?

Hi everybody, As I enjoy the last dregs of summer in Chicago, I bask in the nearly-perfect pre-winter weather, the joy in returning my kids to school, ......
What Reading makes happy you

Proj CDeepFuzz Paper Reading: Metamorphic Testing of Deep Learning Compilers

## Abstract 背景：Compiling DNN models into high-efficiency executables is not easy: the compilation procedure often involves converting high-level model ......
Metamorphic CDeepFuzz Compilers Learning Reading

解决npm ERR! Cannot read properties of null (reading ‘pickAlgorithm‘)报错问题

转载自：https://www.cnblogs.com/zhyp/p/16920380.html 解决方法：在终端中运行命令：npm cache clear --force 然后重新运行 npm i 命令，再次安装安装完成，没有出现报错npm run serve 运行项目，项目可以正常启动了。 安装 ......
pickAlgorithm properties reading Cannot 问题

Proj CDeepFuzz Paper Reading: A Comprehensive Study of Deep Learning Compiler Bugs

## Abstract 背景：深度学习编译器处理的深度学习模型与命令式程序有根本的不同，因为深度学习模型中的程序逻辑是隐式的。（the DL models processed by DL compilers differ fundamentally from imperative programs ......
Comprehensive CDeepFuzz Compiler Learning Reading

Proj CDeepFuzz Paper Reading: DeepMutation: Mutation Testing of Deep Learning Systems

## Abstract 本文：DeepMutation Github: https://github.com/berkuva/mutation-testing-for-DNNs Task: mutation testing framework specialized for DL systems t ......
DeepMutation CDeepFuzz Mutation Learning Reading

Proj CDeepFuzz Paper Reading: Testing Deep Neural Networks

## Abstract 本文:DeepCover Github: https://github.com/TrustAI/DeepCover Task: propose 4 novel test criteria to test DNNs Method: inspired by MC/DC cover ......
CDeepFuzz Networks Reading Testing Neural

Proj CDeepFuzz Paper Reading: TensorFlow: a system for Large-Scale machine learning

## Abstract 本文:Tensorflow Github: https://github.com/tensorflow/tensorflow Task: Detail on Tensorflow dataflow model 特点: 1. operates at large scale an ......
Large-Scale TensorFlow CDeepFuzz learning Reading

Proj CDeepFuzz Paper Reading: SparseProp: Efficient Sparse Backpropagation for Faster Training of Neural Networks

## Abstract 本文：SparseProp Github: https://github.com/IST-DASLab/sparseprop Task: a back-propagation algo for sparse training data, a fast vectorized i ......
Backpropagation SparseProp CDeepFuzz Efficient Networks

Proj CDeepFuzz Paper Reading: PyTorch: an imperative style, high-performance deep learning library

## Abstract 本文： PyTorch Task: detail the implementation and architecture of PyTorch Github: https://github.com/pytorch/pytorch 特点： 1. PyTorch同时关注可用性和速 ......
high-performance performance imperative CDeepFuzz learning

Proj CDeepFuzz Paper Reading: Software Testing with Large Language Model: Survey, Landscape, and Vision

## Abstract 本文: Task: Review on the use of LLMs in software testing Method: 1. analyzes 52 relevant studies ## 1. Intro ![](https://img2023.cnblogs.co ......
CDeepFuzz Landscape Language Software Reading

docker启动mysql报错Can't read dir of '/etc/mysql/conf.d/'

执行命令： docker run -p 3306:3306 --privileged=true -v /mysql/data:/var/lib/mysql -v /mysql/log:/var/log/mysql -v /mysql/conf:/etc/mysql-e MYSQL_ROOT_PASS ......
mysql 39 docker conf read

Proj CDeepFuzz Paper Reading: PELICAN: Exploiting Backdoors of Naturally Trained Deep Learning Models In Binary Code Analysis

## Abstract 背景： 1. 本文研究的不是被恶意植入的后门，而是products of defects in training 2. 攻击模式: injecting some small fixed input pattern(backdoor) to induce misclassifi ......
Exploiting CDeepFuzz Backdoors Naturally Analysis

Proj CDeepFuzz Paper Reading: Decompiling x86 Deep Neural Network Executables

## Abstract 本文: BTD github: https://github.com/monkbai/DNN-decompiler/ Task: a decompiler for DNN models to output DNN specifications including: opera ......
Decompiling Executables CDeepFuzz Network Reading

Python文件读取方法：read()、readline()和readlines()的区别

![在这里插入图片描述](https://img-blog.csdnimg.cn/1bab73a81f954fbabbe802c443e6aa39.png) 在Python中，读取文件是一项常见的任务。Python提供了多种方法来读取文件内容，其中包括read()、readline()和readli ......
readlines readline 文件 方法 Python

CF1374E2 Reading Books(hard version) 题解

# CF1374E2 Reading Books(hard version) 这道题是在 [CF1374E1 Reading Books(easy version)](https://www.luogu.com.cn/problem/CF1374E1) 的基础上出的，而且仅仅增加了一个 $m$ 的限 ......
题解 Reading version 1374E Books

通过ENQUEUE_READ判断单据是否被锁定

## 使用场景 公司的外向交货单需要传到WMS进入出库操作，传输成功后调用BAPI外向交货单的一个状态,如果不判断单据是否被锁定，那么下传wms成功后改变单据状态时就会报错，进而导致状态修改失败，从而导致wms和SAP数据不一致的问题。 ## 解决方式 通过ENQUEUE_READ函数判断某个单据是 ......
单据 ENQUEUE_READ ENQUEUE READ

Proj CDeepFuzz Paper Reading: Balancing Effectiveness and Flakiness of Non-Deterministic Machine Learning Tests

## Abstract 背景：In fact, some of the latest findings suggest that the existence of adversarial attacks may be an inherent weakness of deep learning mod ......
Non-Deterministic Effectiveness Deterministic CDeepFuzz Balancing

Proj CDeepFuzz Paper Reading: NeuRI: Diversifying DNN Generation via Inductive Rule Inference

## Abstract 背景：The correctness of DL systems is crucial for trust in DL applications 本文: NeuRI BaseTool: FreeFuzz Github: https://github.com/ise-uiuc/ ......
Diversifying Generation CDeepFuzz Inductive Inference

Proj CDeepFuzz Paper Reading: Natural attack for pre-trained models of code

## Abstract 背景：目前大多数的adversarial attack method on pre-trained models of code忽略了perturbations should be natural to human judges(naturalness requirement ......
pre-trained CDeepFuzz Natural Reading trained

Proj CDeepFuzz Paper Reading: COMET: Coverage-guided Model Generation For Deep Learning Library Testing

## Abstract 背景：已有的方法(Muffin, Lemon, Cradle) can cover at most 34.1% layer inputs, 25.9% layer parameter values, and 15.6% layer sequences. 本文：COMET Gi ......
Coverage-guided Generation CDeepFuzz Coverage Learning

Proj CDeepFuzz Paper Reading: IvySyn: Automated Vulnerability Discovery in Deep Learning Frameworks

## Abstract 本文：IvySyn Task: discover memory error vulnerabilities in DL frameworks BugType: memory safety errors, fatal runtime errors Method: 1. 利用na ......
Vulnerability Frameworks CDeepFuzz Automated Discovery

MAPF Paper Reading Note

随便写写记录一下 ## 1. 2005-Cooperative Pathfinding ### 1.1. LRA* local repair A* - 依次做A* - 即将开始碰撞时，replan - a general replan solution: 每次重规划时，新增noise，按照比例加入$ ......
Reading Paper MAPF Note

Proj CDeepFuzz Paper Reading: Invariance-inducing regularization using worst-case transformations suffices to boost accuracy and spatial robustness

## Abstract 本文： Task: 1. prove invariance-inducing regularizers can increase predictive accuracy for worst-case spatial transformations 2. prove that ......
Invariance-inducing transformations regularization Invariance robustness

Proj CDeepFuzz Paper Reading: Framework for Evaluating Faithfulness of Local Explanations

## Abstract 本文: Task: 1. study the faithfulness of an explanation system to the underlying prediction model on consistency and sufficiency 2. introduc ......
Faithfulness Explanations Evaluating CDeepFuzz Framework

Proj CDeepFuzz Paper Reading: Differential Testing of Cross Deep Learning Framework APIs: Revealing Inconsistencies and Vulnerabilities

## Abstract 背景：目前对cross-framework conversion中的inconsistencies和security bugs的研究少有 本文：TensorScope Task: test cross-frame APIs in Machine Learning Librar ......
Inconsistencies Vulnerabilities Differential CDeepFuzz Framework
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