UFLDL Tutorial
From Ufldl
(Difference between revisions)
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* [[Self-Taught Learning]] | * [[Self-Taught Learning]] | ||
* [[Image classification]] (talk about how to extract features from a large image) | * [[Image classification]] (talk about how to extract features from a large image) | ||
+ | * [[Softmax regression]] | ||
* [[Exercise:Self-Taught Learning]] | * [[Exercise:Self-Taught Learning]] | ||
Revision as of 20:56, 10 April 2011
Sparse Autoencoder
- Neural Networks
- Backpropagation Algorithm
- Gradient checking and advanced optimization
- Autoencoders and Sparsity
- Visualizing a Trained Autoencoder
- Sparse Autoencoder Notation Summary
- Exercise:Sparse_Autoencoder
Vectorized implementation
- Vectorization
- Logistic Regression Vectorization Example
- Neural Network Vectorization
- Using the MNIST Dataset
- Exercise:Vectorization
Preprocessing: PCA and Whitening
Self-Taught Learning and Unsupervised Feature Learning
- Unsupervised Feature Learning
- Self-Taught Learning
- Image classification (talk about how to extract features from a large image)
- Softmax regression
- Exercise:Self-Taught Learning
Fine-tuning - Exercise: Experiment with and without pre-training
Stacked Autoencoders
Fine-tuning Stacked AEs
Convolutional models (1 layer)
Pooling
Multiple layers of convolution and pooling
Advanced Topics:
RBM
DBN
K-means
Spatial pyramids??
SFA
ICA/TICA/TCNN