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Introduction
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Classroom Contents
From Associative Memories to Deep Networks and From Associative Memories to Universal Machines
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- 1 Introduction
- 2 Associative Memories
- 3 Deep Networks as Memories
- 4 Deep Networks as Kernels
- 5 Deep Networks as Lookup Tables
- 6 Limitations of Deep Networks
- 7 What could the evolution have discovered
- 8 Summary
- 9 Introductions
- 10 The main roadblock
- 11 The grandmother myth
- 12 Jennifer Aniston cells
- 13 Recurrent nets
- 14 Assembly operations
- 15 How powerful is it
- 16 Ray of English
- 17 Neural Basis of Language
- 18 Will shadow nets be equal to deep nets
- 19 How do branches learn
- 20 Robustness
- 21 plasticity rules
- 22 Perceptron and multiplicative
- 23 Representations
- 24 Conclusion
- 25 Question from Xiao
- 26 Question from Zhao
- 27 Question from DeGhani
- 28 Experiments
- 29 Working Memory
