Neural networks and principal component analysis: Learning from examples without local minima
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- Deep learning in neural networks: An overview→Neural networks and principal component analysis: Learning from examples without local mi…Legacy edge — source detail unavailable
- Survey of Clustering Algorithms→Neural networks and principal component analysis: Learning from examples without local mi…Legacy edge — source detail unavailable
- Neural Networks and the Bias/Variance Dilemma→Neural networks and principal component analysis: Learning from examples without local mi…Legacy edge — source detail unavailable
- Optimal unsupervised learning in a single-layer linear feedforward neural network→Neural networks and principal component analysis: Learning from examples without local mi…Legacy edge — source detail unavailable
- Neural networks and principal component analysis: Learning from examples without local mi…→Learning Internal Representations by Error PropagationLegacy edge — source detail unavailable
- Neural networks and principal component analysis: Learning from examples without local mi…→An introduction to computing with neural netsLegacy edge — source detail unavailable
- Neural networks and principal component analysis: Learning from examples without local mi…→Simplified neuron model as a principal component analyzerLegacy edge — source detail unavailable
- Neural networks and principal component analysis: Learning from examples without local mi…→Auto-association by multilayer perceptrons and singular value decompositionLegacy edge — source detail unavailable
- Auto-association by multilayer perceptrons and singular value decomposition→An introduction to computing with neural netsLegacy edge — source detail unavailable
- Auto-association by multilayer perceptrons and singular value decomposition→Learning Internal Representations by Error PropagationLegacy edge — source detail unavailable
- Deep learning in neural networks: An overview→Neural Networks and the Bias/Variance DilemmaLegacy edge — source detail unavailable
- Deep learning in neural networks: An overview→Learning Internal Representations by Error PropagationLegacy edge — source detail unavailable
- Neural Networks and the Bias/Variance Dilemma→Auto-association by multilayer perceptrons and singular value decompositionLegacy edge — source detail unavailable
- Neural Networks and the Bias/Variance Dilemma→An introduction to computing with neural netsLegacy edge — source detail unavailable
- Neural Networks and the Bias/Variance Dilemma→Learning Internal Representations by Error PropagationLegacy edge — source detail unavailable
- Optimal unsupervised learning in a single-layer linear feedforward neural network→Auto-association by multilayer perceptrons and singular value decompositionLegacy edge — source detail unavailable
- Optimal unsupervised learning in a single-layer linear feedforward neural network→An introduction to computing with neural netsLegacy edge — source detail unavailable
- Optimal unsupervised learning in a single-layer linear feedforward neural network→Simplified neuron model as a principal component analyzerLegacy edge — source detail unavailable
- Optimal unsupervised learning in a single-layer linear feedforward neural network→Learning Internal Representations by Error PropagationLegacy edge — source detail unavailable
What this paper cites, inside the corpus
What cites it, inside the corpus
| Paper | Year | Cited |
|---|---|---|
| Deep learning in neural networks: An overview | 2014 | 18,236 |
| Survey of Clustering Algorithms | 2005 | 6,210 |
| Neural Networks and the Bias/Variance Dilemma | 1992 | 3,612 |
| Optimal unsupervised learning in a single-layer linear feedforward neural network | 1989 | 1,533 |
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Topics
| Neural Networks and Applications | Computer Science |
| Model Reduction and Neural Networks | Physics and Astronomy |
| Blind Source Separation Techniques | Computer Science |
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