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<a href="/2015/02/26/近期DL重要论文整理长期更新/" title="近期DL重要论文整理长期更新" itemprop="url">
<time datetime="2015-02-26T08:27:16.000Z" itemprop="datePublished">2015-02-26</time>
<h1 itemprop="name">近期DL重要论文整理长期更新</h1>
<p itemprop="description" >非线性单元：Maxout Ian J Goodfellow, David Warde-Farley, Mehdi Mirza, Aaron Courville, and Yoshua Bengio. Maxout networks. arXiv preprint arXiv:13</p>
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<section class="post" itemscope itemprop="blogPost">
<a href="/2015/02/20/《Deep-Learning》-Bengio-读书笔记3-CNN/" title="《Deep Learning》(Bengio)读书笔记3-CNN" itemprop="url">
<time datetime="2015-02-20T08:23:22.000Z" itemprop="datePublished">2015-02-20</time>
<h1 itemprop="name">《Deep Learning》(Bengio)读书笔记3-CNN</h1>
<p itemprop="description" >此书尚未出版，该笔记仅供学习参考，原文见http://www.iro.umontreal.ca/~bengioy/dlbook/
Convolutional NetworksThe convolution operationToeplitz matrix, Circulant m</p>
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<section class="post" itemscope itemprop="blogPost">
<a href="/2015/02/20/《Deep-Learning》-Bengio-读书笔记2-ML基本知识/" title="《Deep Learning》(Bengio)读书笔记2-ML基本知识" itemprop="url">
<time datetime="2015-02-20T07:43:28.000Z" itemprop="datePublished">2015-02-20</time>
<h1 itemprop="name">《Deep Learning》(Bengio)读书笔记2-ML基本知识</h1>
<p itemprop="description" >此书尚未出版，该笔记仅供学习参考，原文见http://www.iro.umontreal.ca/~bengioy/dlbook/
Machine Learning Basics本部分介绍机器学习的基本概念。
what is learning?Definition of learn</p>
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<section class="post" itemscope itemprop="blogPost">
<a href="/2015/02/20/《Deep-Learning》-Bengio-读书笔记1-DL简介/" title="《Deep Learning》(Bengio)读书笔记1-DL简介" itemprop="url">
<time datetime="2015-02-20T07:43:28.000Z" itemprop="datePublished">2015-02-20</time>
<h1 itemprop="name">《Deep Learning》(Bengio)读书笔记1-DL简介</h1>
<p itemprop="description" >此书尚未出版，该笔记仅供学习参考，原文见http://www.iro.umontreal.ca/~bengioy/dlbook/
[P2]早期的AI是以IBM为的深蓝代表一类的简单的AI。
人的知识与经验是主观和直觉的，因此难以用一种正式的方法表达出来。电脑却恰恰需要各种形式的知</p>
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<section class="post" itemscope itemprop="blogPost">
<a href="/2015/02/12/Caffe学习笔记6-Caffe结构简析（知乎同步）/" title="Caffe学习笔记6-Caffe结构简析（知乎同步）" itemprop="url">
<time datetime="2015-02-12T08:53:57.000Z" itemprop="datePublished">2015-02-12</time>
<h1 itemprop="name">Caffe学习笔记6-Caffe结构简析（知乎同步）</h1>
<p itemprop="description" >来自本人的知乎回答，全文同步
我是从Torch7转移到Caffe的人，仅供参考，当你阅读前你应该具备一些有关DL的基础知识，本文集中写Caffe代码结构而非介绍DL知识。我是去年底开始看Caffe代码的，看代码的时间加在一起也不到一个月，也算半个新手，我的回答是从新手角度作一个入</p>
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<a href="/2015/01/02/Caffe学习笔记5-BLAS与boost-thread加速/" title="Caffe学习笔记5-BLAS与boost::thread加速" itemprop="url">
<time datetime="2015-01-02T08:53:57.000Z" itemprop="datePublished">2015-01-02</time>
<h1 itemprop="name">Caffe学习笔记5-BLAS与boost::thread加速</h1>
<p itemprop="description" >Caffe中运用了大量的优化方法，最近在优化自己代码时候恰好运用了其中的BLAS和Boost::thread。使用过程中遇到了不少问题，这里把我遇到的问题和解决方法整理一下。
BLAS是什么？BLAS (Basic Linear Algebra Subprograms)基础线性代</p>
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<a href="/2014/12/14/Caffe学习笔记4-caffe安装需要注意的libraries/" title="Caffe学习笔记4-caffe安装需要注意的libraries" itemprop="url">
<time datetime="2014-12-14T02:58:09.000Z" itemprop="datePublished">2014-12-14</time>
<h1 itemprop="name">Caffe学习笔记4-caffe安装需要注意的libraries</h1>
<p itemprop="description" >当调用caffe训练数据的时候实际上调用的文件是在caffe.cpp中实现的train() 和 test()两个函数。搞清楚这两个函数对caffe的调用过程很有帮助。在这之前要提到几个相关的库，虽然与caffe实现关系不大，但完全不懂还是多少有点影响代码的理解。
Google C</p>
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<a href="/2014/12/09/Caffe学习笔记3-Layer的相关学习/" title="Caffe学习笔记3-Layer的相关学习" itemprop="url">
<time datetime="2014-12-09T15:18:14.000Z" itemprop="datePublished">2014-12-09</time>
<h1 itemprop="name">Caffe学习笔记3-Layer的相关学习</h1>
<p itemprop="description" >LayerLayer是所有层的基类，在Layer的基础上衍生出来的有5种Layers：
data_layer
neuron_layer
loss_layer
common_layer
vision_layer
它们都有对应的[.hpp .cpp]文件声明和实现了各个类的接口。</p>
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<a href="/2014/12/09/Caffe学习笔记2-Caffe的三级结构-Blobs-Layers-Nets/" title="Caffe学习笔记2-Caffe的三级结构(Blobs,Layers,Nets)" itemprop="url">
<time datetime="2014-12-09T11:53:35.000Z" itemprop="datePublished">2014-12-09</time>
<h1 itemprop="name">Caffe学习笔记2-Caffe的三级结构(Blobs,Layers,Nets)</h1>
<p itemprop="description" >根据Caffe官方文档介绍，caffe大致可以分为三层结构blob，layer，net。数据的保存，交换以及操作都是以blob的形式进行的，layer是模型和计算的基础，net整和并连接layer。
BlobsBlob是Caffe的基本数据结构，具有CPU和GPU之间同步的能力,</p>
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<section class="post" itemscope itemprop="blogPost">
<a href="/2014/12/09/Caffe学习笔记1-安装以及代码结构/" title="Caffe学习笔记1-安装以及代码结构" itemprop="url">
<time datetime="2014-12-09T11:51:36.000Z" itemprop="datePublished">2014-12-09</time>
<h1 itemprop="name">Caffe学习笔记1-安装以及代码结构</h1>
<p itemprop="description" >安装按照官网教程安装，我在 OS X 10.9 和 Ubuntu 14.04 上面都安装成功了。主要麻烦在于 glog gflags gtest 这几个依赖项是google上面的需要翻墙。由于我用Mac没有CUDA，所以安装时需要设置 CPU_ONLY := 1。
如果不是干净的</p>
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<li><a href="/categories/Book/" title="Book">Book<sup>3</sup></a></li>
<li><a href="/categories/Code/" title="Code">Code<sup>1</sup></a></li>
<li><a href="/categories/LearningCaffe/" title="LearningCaffe">LearningCaffe<sup>6</sup></a></li>
<li><a href="/categories/Note/" title="Note">Note<sup>3</sup></a></li>
<li><a href="/categories/Paper/" title="Paper">Paper<sup>2</sup></a></li>
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<li><a href="/tags/BLAS/" title="BLAS">BLAS<sup>1</sup></a></li>
<li><a href="/tags/Boost/" title="Boost">Boost<sup>1</sup></a></li>
<li><a href="/tags/CNN/" title="CNN">CNN<sup>1</sup></a></li>
<li><a href="/tags/Caffe/" title="Caffe">Caffe<sup>6</sup></a></li>
<li><a href="/tags/DeepNet/" title="DeepNet">DeepNet<sup>1</sup></a></li>
<li><a href="/tags/Optim/" title="Optim">Optim<sup>1</sup></a></li>
<li><a href="/tags/PCANet/" title="PCANet">PCANet<sup>1</sup></a></li>
<li><a href="/tags/Thread/" title="Thread">Thread<sup>1</sup></a></li>
<li><a href="/tags/Torch/" title="Torch">Torch<sup>2</sup></a></li>
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<a href="/tags/BLAS/" style="font-size: 10px;">BLAS</a> <a href="/tags/Boost/" style="font-size: 10px;">Boost</a> <a href="/tags/CNN/" style="font-size: 10px;">CNN</a> <a href="/tags/Caffe/" style="font-size: 20px;">Caffe</a> <a href="/tags/DeepNet/" style="font-size: 10px;">DeepNet</a> <a href="/tags/Optim/" style="font-size: 10px;">Optim</a> <a href="/tags/PCANet/" style="font-size: 10px;">PCANet</a> <a href="/tags/Thread/" style="font-size: 10px;">Thread</a> <a href="/tags/Torch/" style="font-size: 13.33px;">Torch</a> <a href="/tags/《Deep-Learning》/" style="font-size: 16.67px;">《Deep Learning》</a>
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