silas_xue的专栏

Facebook AI Research的Yann Le Cun 在nips 2016上Predictive Learning 的tutorial演讲ppt，来自于google docs ，https://drive.google.com/file/d/0BxKBnD5y2M8NREZod0tVdW5FLTQ/view

Spark亚太研究院王家林的《大数据Spark企业级实战》pdf文件，虽是扫描版本，但带标签，清晰度很高。来自于CSDN需要积分下载的链接，http://download.csdn.net/detail/sophiander/9646573。感谢分享。

Spark亚太研究院王佳林的《大数据Spark企业级实战》pdf文件，虽是扫描版本，但带标签，清晰度很高。

最新的中国计算机学会推荐国际学术刊物与期刊目录，2015年。另含相对于上一版目录新增的期刊与会议列表。

This book consists of six chapters, which can be grouped into three subjects. The first subject is Machine Learning and takes place in Chapter 1. Deep Learning stems from Machine Learning. This implies that if you want to understand the essence of Deep Learning, you have to know the philosophy behind Machine Learning to some extent. Chapter 1 starts with the relationship between Machine Learning and Deep Learning, followed by problem solving strategies and fundamental limitations of Machine Learning. The detailed techniques are not introduced yet. Instead, fundamental concepts that applies to both the neural network and Deep Learning will be covered. The second subject is artificial neural network. Chapters 2-4 focuses on this subject. As Deep Learning is a type of Machine Learning that employs a neural network, the neural network is inseparable from Deep Learning. Chapter 2 starts with the fundamentals of the neural network: principles of its operation, architecture, and learning rules. It also provides the reason that the simple single-layer architecture evolved to the complex multi-layer architecture. Chapter 3 presents the backpropagation algorithm, which is an important and representative learning rule of the neural network and also employed in Deep Learning. This chapter explains how cost functions and learning rules are related and which cost functions are widely employed in Deep Learning. Chapter 4 introduces how to apply the neural network to classification problems. We have allocated a separate section for classification because it is currently the most prevailing application of Machine Learning. For example, image recognition, one of the primary applications of Deep Learning, is a classification problem. The third topic is Deep Learning. It is the main topic of this book as well. Deep Learning is covered in Chapters 5 and 6. Chapter 5 introduces the drivers that enables Deep Learning to yield excellent performance. For a better understanding, it starts with the history of barriers and solutions of Deep Learning. Chapter 6 covers the convolution neural network, which is representative of Deep Learning techniques. The convolution neural network is second-to-none in terms of image recognition. This chapter starts with an introduction of the basic concept and architecture of the convolution neural network as it compares with the previous image recognition algorithms. It is followed by an explanation of the roles and operations of the convolution layer and pooling layer, which act as essential components of the convolution neural network. The chapter concludes with an example of digit image recognition using the convolution neural network and investigates the evolution of the image throughout the layers.

Deep Learning Book, by Yoshua Bengio, Ian Goodfellow, Aaron Courville @October 03, 2015

基于最大间隔的度量学习代码，对学习判别性的度量学习算法有益。

2011年，答辩PPT范例，清晰明了，值得借鉴。

沿着目标外观建模的思路，对目标跟踪的最新成果进行了综述，发表于ACM Transactions on Intelligent Systems and Technology，2013年。

视觉跟踪算法综述_杨戈，10年的中文综述，补充了Yilmaz在ACM Comput.Surv的之后新出现的内容。

视觉跟踪技术综述_侯志强，06年的中文综述，对Yilmaz在ACM Comput.Surv的内容进行了扩展和补充。

来自网友整理的有关JNI开发的资料，对于Android NDK开发有不小的帮助。

刘维的那本，这里是第2部分。 本书主要介绍如何运用Matlab与C/C++进行混合程序设计。本书全面详细介绍了Matlab C数学库、Matlab C++数学库、Matcom、Matlab COM Builder、Matlab Engine及编译Matlab独立可执行程序等Matlab混合程序设计的内容。.

刘维的那本,这里第1部分，还有第2部分，请注意查找链接。 本书主要介绍如何运用Matlab与C/C++进行混合程序设计。本书全面详细介绍了Matlab C数学库、Matlab C++数学库、Matcom、Matlab COM Builder、Matlab Engine及编译Matlab独立可执行程序等Matlab混合程序设计的内容。

很多ebook网站的链接都失效了，发上来大家一同学习,Springer的那本。看看N.Sebe, Ira Cohen, Ashutosh Garg和Thomas S. Huang是怎么看计算机视觉中的机器学习问题的。

很多ebook网页的链接都失效了，发上来共享给大家。看一下N. SEBE和T.HUANG是怎么看CV中的ML问题的。

张尧学的书很棒 清华的书 质量一向都很好 很不容易从同学那里传过来的 张尧学 - 计算机操作系统教程(第二版)(带习题答案和实验指导)

《操作系统教程》（第三版） 孙钟秀主编 费翔林 骆斌 谢立参编 高教的那本 网上好像很少 所以上传 大家共享一下

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Compressed sensing 方面的有用文献 PPT

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Remark in Compressed sensing