master
所属分类：Java编程
开发工具：Visual C++
文件大小：54KB
下载次数：420
上传日期：2013-05-05 17:20:49
上 传 者：
samkuok
说明： 深度学习各种版本代码，包括C,C++,JAVA,python,scala
(many versions of deep learning code,include versions of C,C++,JAVA,python,scala)
文件列表:
c (0, 2013-03-27)
c\DBN.c (15138, 2013-03-27)
c\DBN.h (440, 2013-03-27)
c\HiddenLayer.h (391, 2013-03-27)
c\LogisticRegression.c (3303, 2013-03-27)
c\LogisticRegression.h (500, 2013-03-27)
c\RBM.c (5842, 2013-03-27)
c\RBM.h (613, 2013-03-27)
c\SdA.c (15299, 2013-03-27)
c\SdA.h (441, 2013-03-27)
c\dA.c (5508, 2013-03-27)
c\dA.h (481, 2013-03-27)
c\utils.h (124, 2013-03-27)
cpp (0, 2013-03-27)
cpp\DBN.cpp (12429, 2013-03-27)
cpp\DBN.h (345, 2013-03-27)
cpp\HiddenLayer.cpp (1422, 2013-03-27)
cpp\HiddenLayer.h (237, 2013-03-27)
cpp\LogisticRegression.cpp (3135, 2013-03-27)
cpp\LogisticRegression.h (270, 2013-03-27)
cpp\RBM.cpp (4913, 2013-03-27)
cpp\RBM.h (484, 2013-03-27)
cpp\SdA.cpp (12721, 2013-03-27)
cpp\SdA.h (346, 2013-03-27)
cpp\dA.cpp (4717, 2013-03-27)
cpp\dA.h (382, 2013-03-27)
cpp\utils.cpp (417, 2013-03-27)
java (0, 2013-03-27)
java\DBN (0, 2013-03-27)
java\DBN\src (0, 2013-03-27)
java\DBN\src\DBN.java (5746, 2013-03-27)
java\DBN\src\HiddenLayer.java (1458, 2013-03-27)
java\DBN\src\LogisticRegression.java (1320, 2013-03-27)
java\DBN\src\RBM.java (4028, 2013-03-27)
java\LogisticRegression (0, 2013-03-27)
java\LogisticRegression\src (0, 2013-03-27)
java\LogisticRegression\src\LogisticRegression.java (2411, 2013-03-27)
... ...
# Deep Learning (Python, C/C++, Java)
### Classes :
- DBN: Deep Belief Nets
- CDBN: Deep Belief Nets w/ continuous-valued inputs
- RBM: Restricted Boltzmann Machine
- CRBM: Restricted Boltzmann Machine w/ continuous-valued inputs
- dA: Denoising Autoencoders
- SdA: Stacked Denoising Autoencoders
- LogisticRegression: Logistic Regression
- HiddenLayer: Hidden Layer of Neural Networks
### References :
- Y. Bengio, P. Lamblin, D. Popovici, H. Larochelle: Greedy Layer-Wise
Training of Deep Networks, Advances in Neural Information Processing
Systems 19, 2007
- P. Vincent, H. Larochelle, Y. Bengio, P.A. Manzagol: Extracting and
Composing Robust Features with Denoising Autoencoders, ICML' 08, 1096-1103,
2008
- DeepLearningTutorials
https://github.com/lisa-lab/DeepLearningTutorials
- Yusuke Sugomori: Stochastic Gradient Descent for Denoising Autoencoders,
http://yusugomori.com/docs/SGD_DA.pdf
### Bug reports are deeply welcome.
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