526互联

Deep

vue中watch侦听器，deep和immediate的用法

1、deep深度监听的用法 当监听一个对象时，可能想监听整个对象的变化，而不仅仅是某个属性。但在默认情况下，如果你正在监听formData对象并且修改了formData.username，对应的侦听器并不会触发，它只在formData对象被整个替换时触发。 监听整个对象被称作深度监听，通过将deep ......
侦听器 immediate watch deep vue

【五期邹昱夫】CCF-B（IEEE Access'19）Badnets: Evaluating backdooring attacks on deep neural networks

> "Gu, Tianyu, et al. "Badnets: Evaluating backdooring attacks on deep neural networks." IEEE Access 7 (2019): 47230-47244." 本文提出了外包机器学习时选择值得信赖的提供商的重要 ......
backdooring Evaluating networks Badnets attacks

【五期邹昱夫】CCF-B（RAID'18）Fine-Pruning: Defending Against Backdooring Attacks on Deep Neural Networks

> "Liu, Kang, Brendan Dolan-Gavitt, and Siddharth Garg. "Fine-pruning: Defending against backdooring attacks on deep neural networks." Research in Att ......
Fine-Pruning Backdooring Defending Networks Against

【五期邹昱夫】CCF-A（NeurIPS'21）Adversarial Neuron Pruning Purifies Backdoored Deep Models

> "Wu, Dongxian, and Yisen Wang. "Adversarial neuron pruning purifies backdoored deep models." Advances in Neural Information Processing Systems 34 (2 ......
Adversarial Backdoored Purifies NeurIPS Pruning

Faster sorting algorithms discovered using deep reinforcement learning

## 摘要： - `AlphaDev`模型优化排序算法，将排序算法提速70％。通过强化学习，AlphaDev发现了更加有效的算法，直接超越了科学家和工程师们几十年来的精心打磨。现在，新的算法已经成为两个标准C++编码库的一部分，每天都会被全球的程序员使用数万亿次。 ## 介绍 - 优化目标为排序算法 ......
reinforcement algorithms discovered learning sorting

《深度学习(deep learning)》pdf电子书免费下载

《深度学习》由全球知名的三位专家Ian Goodfellow、Yoshua Bengio 和Aaron Courville撰写，是深度学习领域奠基性的经典教材。全书的内容包括3个部分：第 1部分介绍基本的数学工具和机器学习的概念，它们是深度学习的预备知识；第 2部分系统深入地讲解现今已成熟的深度学习 ......
电子书 深度 learning 免费下载 电子

选修-4-Optimization for Deep Learning

# 1. Some Nitations 在本小节开始之前,需要知道的符号含义. ![image](https://img2023.cnblogs.com/blog/2264614/202306/2264614-20230604200321926-907208090.png) # 2. What is ......
Optimization Learning Deep for

vue watch deep 用法

### 简单案例 ``` watch deep obj:{{obj}} 调用watch次数:{{times}} 改变对象 ``` ![](https://img2023.cnblogs.com/blog/1202393/202306/1202393-20230614131230156-5873063 ......
watch deep vue

Vue-watch-deep 深度监听

首先明确一个概念，Vue 是可以监听到 多层级数据改变的，且可以在页面上做出对应展示。但是 Vue 提供的 watch 方法，默认是不提供 深度监听的( deep 默认为 false，也就是不开启深度监听) (刚挂载的时候是不执行的，只有挂载完成之后的变化才会执行。如果我们想要初次挂载的时候就l执行 ......
Vue-watch-deep 深度 watch deep Vue

侦听器-deep选项

```HTML ``` ......
侦听器 deep

nature-deep learning

Title：Deep learning Authors：Yann LeCun Yoshua Bengio & Geoffrey Hinton doi:10.1038/nature14539 # 1. 概述 使用多处理层学习数据不同层次的抽象表示，在语音识别、视觉识别、目标检测，以及药物发明、基因学等 ......
nature-deep learning nature deep

Deep One-Class Classification

# Deep One-Class Classifification Deep SVDD (Deep Support Vector Data Description)训练一个神经网络，最小化包含数据表征的超球的体积（如图1所示） ![image-20230606193307205](https://i ......
Classification One-Class Class Deep One

Deep Isolation Forest for Anomaly Detection

# Deep Isolation Forest for Anomaly Detection ## 1 INTRODUCTION IForest的缺点 - 它的与坐标轴平行的隔离方法会导致它在高维/非线性空间中难以检测到异常。 如图1所示。红色为异常节点，蓝色为正常节点。红色被蓝色所包围，这种情况无法 ......
Isolation Detection Anomaly Forest Deep

事件抽取论文综述-A Survey on Deep Learning Event Extraction: Approaches and Applications

A Survey on Deep Learning Event Extraction: Approaches and Applications 1）发表信息： https://arxiv.org/abs/2107.02126 Qian Li, Jianxin Li, Member, IEEE, Ji ......
Applications Approaches Extraction Learning 事件

The Difficulty of Passive Learning in Deep Reinforcement Learning

![](https://img2023.cnblogs.com/blog/1428973/202305/1428973-20230524224808789-13684847.png) **发表时间：**2021(NeurIPS 2021) **文章要点：**这篇文章提出一个tandem learni ......
Learning Reinforcement Difficulty Passive Deep

Paper Reading: forgeNet a graph deep neural network model using tree-based ensemble classifiers for feature graph construction

[toc] Paper Reading 是从个人角度进行的一些总结分享，受到个人关注点的侧重和实力所限，可能有理解不到位的地方。具体的细节还需要以原文的内容为准，博客中的图表若未另外说明则均来自原文。 | 论文概况 | 详细 | | | | | 标题 | 《forgeNet: a graph dee ......
graph construction classifiers tree-based forgeNet

Off-Policy Deep Reinforcement Learning without Exploration

**发表时间：**2019（ICML 2019） **文章要点：**这篇文章想说在offline RL的setting下，由于外推误差（extrapolation errors）的原因，标准的off-policy算法比如DQN，DDPG之类的，如果数据的分布和当前policy的分布差距很大的话，那就 ......
Reinforcement Exploration Off-Policy Learning without

【图像数据增强】Image Data Augmentation for Deep Learning: A Survey

| 原始题目 | Image Data Augmentation for Deep Learning: A Survey | | | | | 中文名称 | 深度学习的图像数据增强:综述 | | 发表时间 | 2022年4月19日 | | 平台 | arXiv | | 来源 | 南京大学 | | 文章 ......
Augmentation Learning 图像 数据 Survey

Robust Deep Reinforcement Learning through Adversarial Loss

郑重声明：原文参见标题，如有侵权，请联系作者，将会撤销发布！ 35th Conference on Neural Information Processing Systems (NeurIPS 2021) Abstract 最近的研究表明，深度强化学习智能体很容易受到智能体输入上的小对抗性扰动的影响 ......
Reinforcement Adversarial Learning through Robust

Vue watch 的handler,immediate,deep属性

new Vue({ el: '#app', data: { num: 0, sum:10, }, watch: { // 只要num的值发生变化，sum的值就会变化 不用handler的简洁写法 num(newValue, oldValue) { this.sum= newValue; } // 也 ......
immediate 属性 handler watch deep

XCPC真题（2）：Little Tiger vs. Deep Monkey|Greatest Common Divisor|Array Merge

🎈 作者：Eriktse 🎈 简介：19岁，211计算机在读，现役ACM银牌选手🏆力争以通俗易懂的方式讲解算法！❤️欢迎关注我，一起交流C++/Python算法。（优质好文持续更新中……）🚀 🎈 阅读原文获得更好阅读体验：https://www.eriktse.com/algorithm/ ......
真题 Greatest Divisor Little Common

Robust Deep Reinforcement Learning against Adversarial Perturbations on State Observations

郑重声明：原文参见标题，如有侵权，请联系作者，将会撤销发布！ NeurIPS 2020 ......
Reinforcement Perturbations Observations Adversarial Learning

论文阅读-sparse gpu kernels for deep learning

论文地址：https://ieeexplore.ieee.org/document/9355309 源码地址：https://github.com/google-research/sputnik 背景 深度神经网络由大量的矩阵乘法运算和卷积运算组成，这些运算中使用的矩阵可以转化成稀疏矩阵，同时不损失 ......
learning kernels sparse 论文 deep

Deep Dynamics Models for Learning Dexterous Manipulation

**发表时间：**2019 (CoRL 2019) **文章要点：**文章提出了一个online planning with deep dynamics models (PDDM)的算法来学习Dexterous multi-fingered hands，大概意思就是学习拟人的灵活的手指操控技巧。大概 ......
Manipulation Dexterous Dynamics Learning Models

Cluster-GCN An Efficient Algorithm for Training Deep Convolution Networks

Chiang W., Liu X., Si S., Li Y., Bengio S. and Hsieh C. Cluster-GCN: An efficient algorithm for training deep and large graph convolutional networks. ......
Cluster-GCN Convolution Algorithm Efficient Training

Deep-Learning-Based Spatio-Temporal-Spectral Integrated Fusion of Heterogeneous Remote Sensing Images

Deep-Learning-Based Spatio-Temporal-Spectral Integrated Fusion of Heterogeneous Remote Sensing Images abstract 为了解决STF中的生成heterogeneous images问题: 为此，本 ......
Spatio-Temporal-Spectral Deep-Learning-Based Heterogeneous Integrated Learning

Adversarial Robust Deep Reinforcement Learning Requires Redefining Robustness

郑重声明：原文参见标题，如有侵权，请联系作者，将会撤销发布！ ......
Reinforcement Adversarial Redefining Robustness Learning

论文解读（PGD）《Towards deep learning models resistant to adversarial attacks》

论文信息 论文标题：Towards deep learning models resistant to adversarial attacks论文作者：Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, Ad ......
adversarial resistant learning Towards attacks

Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks

Zou D., Hu Z., Wang Y., Jiang S., Sun Y. and Gu Q. Layer-dependent importance sampling for training deep and large graph convolutional networks. NIPS, ......
Layer-Dependent Convolutional Importance Dependent Sampling

阅读文献《SCNet：Deep Learning-Based Downlink Channel Prediction for FDD Massive MIMO System》

该文献的作者是清华大学的高飞飞老师，于2019年11月发表在IEEE COMMUNICATIONS LETTERS上。 文章给出了当用户位置到信道的映射是双射时上行到下行的确定映射函数；还提出了一个**稀疏复值神经网络( sparse complex-valued neural network，SC ......
Learning-Based Prediction 文献 Learning Downlink
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