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. Nested Loops，Hash Join 和 Sort Merge Join. 三种不同连接的不同：

    原文:https://blog.csdn.net/tianlesoftware/article/details/5826546 Nested Loops,Hash Join 和 Sort Merge ...

  2. typeof 和 instanceof 区别

    typeof操作符返回一个字符串,表示未经计算的操作数的类型. 可能返回值有:"undefined"."object"."boolean". ...

  3. struct tm

    struct tm { int tm_sec; /* 秒–取值区间为[0,59] */ int tm_min; /* 分 - 取值区间为[0,59] */ int tm_hour; /* 时 - 取值 ...

  4. swiper 仿淘宝详情页面 视频图片切换

    1.好兄弟,看一下是否是你需要的 2.废话不多说 直接上代码,复制粘贴一下 自己引用一下swiper.js和css 然后就可以开始玩儿了 <!DOCTYPE html> <html& ...

  5. 记遇到的一个php坑

    最近对项目的一个高访问量业务接口进行功能扩展,上线一段时间后,服务器cpu load突然飙升,并出现大量502.一开始找运维查看日志,并没有看是什么问题,后来发现别的部门项目之前也遇到类似的问题,原来 ...

  6. [上架] iOS 上架更新版本号建议

    iOS 上架一個新版本号,就改个版号数字就好,有什么好说的? 是啊~ 如果上架顺利的话,就没什么好说的,如果被退件,再上传更新时,那版号怎么改? 下面说说我的做法(这只是建议,版号随自己喜好,没有固定 ...

  7. C语言read函数的那些坑

    今天在复习UNIX文件系统,用到那个read函数,但是无意中却掉到一个坑里了,用了一个多小时才找到问题根源,这里记录一下. 问题是这样的:我需要使用read和write函数把键盘输入的信息复制到输出. ...

  8. 【 C 】字符串常量

    当一个字符串常量出现在表达式中时,它的值是个指针常量.编译器把这些指定字符的一份拷贝存储在内存的某个位置,并存储一个指向第一个字符的指针.但是,当数组名用于表达式中时,它们的值也是个指针常量.我们可以 ...

  9. 【C】对指针表达式的个人总结与思考

    本文内容参考<c 和 指针>. 声明:本博文只为那些能沉得住气,认真研究,探索真知的人参考,浮躁的人请离开,因为看不懂. 感觉以前学c的时候,学的指针真是白学了,今天看到这个内容,困惑后, ...

  10. VIM - 模式简介

    1. 概述 简述 vim 模式 很简单的东西, 随便说说得了 2. 模式们 概述 vim 各个模式 后面的切换, 都是从 标准模式 切换到其他模式 1. Normal Mode 名称 标准模式 / 常 ...