| 4 |
Training CRFs
- Other suggested readings -
- Papers discussing non-linear conditional random fields:
- Precursor paper on conditional random fields:
- Papers on alternative training methods for conditional random fields:
- Paper describing different methods for taking into account the test-time error function during training:
- Other suggested video material -
| 5 |
Restricted Boltzmann machine
- Other suggested readings -
- Other paper on other approaches for training models with intractable normalization constants:
- Papers on extensions of the restricted Boltzmann machine:
- Papers on more advanced sampling methods:
- Other suggested video material -
|
| 6 |
Autoencoders
- Other suggested readings -
- Theoretical paper demonstrating the optimality results for the linear autoencoder:
- Papers on different extensions of the autoencoder:
|
| 7 |
Deep learning
- Other suggested readings -
- Paper on deep belief networks (DBNs):
- Paper on deep autoencoders:
- Detailed paper on deep learning:
- Experimental evaluations of deep learning methods:
- Papers on alternative approaches for unsupervised pre-training of deep networks:
- Papers on dropout regularisation methods:
- Paper on another type of non-feedfoward deep network:
- Other suggested video material -
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| 8 |
Sparse coding
- Other suggested readings-
- Papers on other sparse representation models:
- Variants of sparse coding models:
- Online sparse coding algorithm:
- Method to accelerate inference in sparse coding model:
- Other suggested video material -
|
| 9 |
Computer vision
- Other suggested readings -
- Experimental evaluation of good practices in using convolutional networks:
- Convolutional version of the restricted Boltzmann machine:
- Summary of the neurophysiology of the visual cortex:
- Analysis of random filters:
- Different applications to computer vision of neural networks:
- Other convolutional systems:
- Other suggested video material -
|
| 10 |
Natural language processing
- Other suggested readings -
- Papers on language modeling with neural networks:
- Modeling documents with neural networks:
- Other papers on word tagging with neural networks:
- Other efficient training algorithms for text data:
- Papers on learning word vector representations:
- Papers on recursive neural network:
-
Parsing Natural Scenes and Natural Language with Recursive Neural Networks
by Richard Socher,
Jeffrey Pennington,
Eric Huang,
Andrew Ng and
Christopher Manning
[video]
-
Semi-Supervised Recursive Autoencoders for Predicting Sentiment Distributions
by Richard Socher,
Jeffrey Pennington,
Eric Huang,
Andrew Ng and
Christopher Manning
-
Dynamic Pooling and Unfolding Recursive Autoencoders for Paraphrase Detection
by Richard Socher,
Eric Huang,
Jeffrey Pennington,
Andrew Ng and
Christopher Manning
-
Semantic Compositionality through Recursive Matrix-Vector Spaces
by Richard Socher,
Brody Huval,
Christopher Manning
and Andrew Ng
- Other suggested video material -
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