Link of the Paper: https://arxiv.org/pdf/1409.3215.pdf

Main Points:

  1. Encoder-Decoder Model: Input sequence -> A vector of a fixed dimensionality -> Target sequence.
  2. A multilayered  LSTM: The LSTM did not have difficulty on long sentences. Deep LSTMs significantly outperformed shallow LSTMs.
  3. Reverse Input: Better performance. While the authors do not have a complete explanation to this phenomenon, they believe that it is caused by the introduction of many short term dependencies to the dataset. LSTMs trained on reversed source sentences did much better on long sentences than LSTMs trained on the raw source sentences, which suggests that reversing the input sentences results in LSTMs with better memory utilization.

Other Key Points:

  1. A significant limitation: Despite their flexibility and power, DNNs can only be applied to problems whose inputs and targets can be sensibly encoded with vectors of fixed dimensionality.

Paper Reading - Sequence to Sequence Learning with Neural Networks ( NIPS 2014 )的更多相关文章

  1. Paper Reading - Deep Captioning with Multimodal Recurrent Neural Networks ( m-RNN ) ( ICLR 2015 ) ★

    Link of the Paper: https://arxiv.org/pdf/1412.6632.pdf Main Points: The authors propose a multimodal ...

  2. 【论文笔记】Learning Convolutional Neural Networks for Graphs

    Learning Convolutional Neural Networks for Graphs 2018-01-17  21:41:57 [Introduction] 这篇 paper 是发表在 ...

  3. PP: Sequence to sequence learning with neural networks

    From google institution; 1. Before this, DNN cannot be used to map sequences to sequences. In this p ...

  4. 《MATLAB Deep Learning：With Machine Learning，Neural Networks and Artificial Intelligence》选记

    一.Training of a Single-Layer Neural Network 1 Delta Rule Consider a single-layer neural network, as ...

  5. [C1W4] Neural Networks and Deep Learning - Deep Neural Networks

    第四周:深层神经网络(Deep Neural Networks) 深层神经网络(Deep L-layer neural network) 目前为止我们学习了只有一个单独隐藏层的神经网络的正向传播和反向 ...

  6. [C1W3] Neural Networks and Deep Learning - Shallow neural networks

    第三周:浅层神经网络(Shallow neural networks) 神经网络概述(Neural Network Overview) 本周你将学习如何实现一个神经网络.在我们深入学习具体技术之前,我 ...

  7. 目标检测--Scalable Object Detection using Deep Neural Networks(CVPR 2014)

    Scalable Object Detection using Deep Neural Networks 作者: Dumitru Erhan, Christian Szegedy, Alexander ...

  8. Sequence to Sequence Learning with Neural Networks论文阅读

    论文下载 作者(三位Google大佬)一开始提出DNN的缺点,DNN不能用于将序列映射到序列.此论文以机器翻译为例,核心模型是长短期记忆神经网络(LSTM),首先通过一个多层的LSTM将输入的语言序列 ...

  9. Paper Reading——LEMNA:Explaining Deep Learning based Security Applications

    Motivation: The lack of transparency of the deep  learning models creates key barriers to establishi ...

随机推荐

  1. IT经理苏大强：我不吃，我不喝，我要赶项目！

    IT经理老苏的日常 1周,2周,3周 -- 为了公司的发展和孩子的奥利奥 这点短痛不算什么 Iron Cloud 微服务开发云[www.ironz.com] 高效满足业务需求 高速交付 驱动增长

  2. 协议类接口 - NAND

    一.引脚的含义 先看下nand flash是怎么接的,如下所示便为某一款nand存储芯片的引脚图.发现其连地址信号都没有.那么是如何访问地址数据的呢? 查阅该nand flash的数据手册可得其各个引 ...

  3. 截屏状态监听 - iOS

    既接到电话状态监听的需求之后再次添加了截屏状态的监听,当使用 App 时若用户执行截屏操作需要对当前状态进行监听操作,下面有两种方法,其中可以替换截屏的图片内容(Plan A),也可以弹出提示框(Pl ...

  4. CABasicAnimation使用总结

    CABasicAnimation使用总结 实例化 使用方法animationWithKeyPath:对 CABasicAnimation进行实例化,并指定Layer的属性作为关键路径进行注册. //围 ...

  5. iOS 百度地图判断用户是否拖动地图的检测方法

    前言:百度地图API并没有提供移动地图时的回调接口 实现:通过判断当前地图的中心位置是否为用户位置来判断,代码如下 -(void)mapView:(BMKMapView *)mapView regio ...

  6. redis 安装 配置 及启动

    linux下安装redis及其中遇到的问题的解决方法1.将下载好的压缩包放到/usr/local目录下# tar xzf redis-3.0.2.tar.gz# cd redis-3.0.2# mak ...

  7. vue项目获取当前地址栏参数（非路由传参）

    项目中遇到一个需求,就是另一个管理系统带参直接单纯的跳转跳转到vue pc项目中的某个页面,后再初始化查询数据,参数以地址栏的形式传入 管理系统:打开新地址地址 let obj = { id: 21, ...

  8. 误卸载glibc类库导致系统崩溃解决方案

    由于系统中没有yum环境需要编译安装redis,但系统中却没有安装gcc和gcc-c++,挂载本地镜像安装gcc和gcc-c++由于版本太高,由于一时疏忽误将系统的依赖库glibc使用rpm -e 命 ...

  9. Linux查看当前登录用户并踢出用户

    1.查看当前登录用户 [wilsh@lcl ~]$ whatis w w                    (1)  - Show who is logged on and what they a ...

  10. 【五】安装fcig

    安装fcig 安装fcig 此步骤是为了让spawn-fcgi能够识别自定义的demo 编译文件 自定义c文件 测试成功后,启动spawn cgi进行代理托管 此步骤是为了让spawn-fcgi能够识 ...