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Book Categories |
| 1 | Introduction | 1 |
| 2 | Recurrent and Folding Networks | 5 |
| 2.1 | Definitions | 5 |
| 2.2 | Training | 11 |
| 2.3 | Backround | 13 |
| 2.4 | Applications | 15 |
| 3 | Approximation Ability | 19 |
| 3.1 | Foundations | 20 |
| 3.2 | Approximation in Probability | 25 |
| 3.3 | Approximation in the Maximum Norm | 36 |
| 3.4 | Discussion and Open Questions | 48 |
| 4 | Learnability | 51 |
| 4.1 | The Learning Scenario | 53 |
| 4.2 | PAC Learnability | 63 |
| 4.3 | Bounds on the VC-Dimension of Folding Networks | 79 |
| 4.4 | Consequences for Learnability | 93 |
| 4.5 | Lower Bounds for the LRAAM | 97 |
| 4.6 | Discussion and Open Questions | 98 |
| 5 | Complexity | 103 |
| 5.1 | The Loading Problem | 105 |
| 5.2 | The Perceptron Case | 110 |
| 5.3 | The Sigmoidal Case | 122 |
| 5.4 | Discussion and Open Questions | 130 |
| 6 | Conclusion | 133 |
| Bibliography | 137 | |
| Index | 145 |
| Price | Condition | Delivery | Seller | Action |
| $121.44 | Digital |
| WonderClub |
Ol Hat
reviewed Learning With Recurrent Neural Networks on September 04, 2018
Learning With Recurrent Neural Networks
Fascinating read but quite outdated
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Add Learning With Recurrent Neural Networks, Folding networks, a generalisation of recurrent neural networks to tree structured inputs, are investigated as a mechanism to learn regularities on classical symbolic data, for example. The architecture, the training mechanism, and several applications in, Learning With Recurrent Neural Networks to the inventory that you are selling on WonderClubX
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Add Learning With Recurrent Neural Networks, Folding networks, a generalisation of recurrent neural networks to tree structured inputs, are investigated as a mechanism to learn regularities on classical symbolic data, for example. The architecture, the training mechanism, and several applications in, Learning With Recurrent Neural Networks to your collection on WonderClub |
