Difference between revisions of "Neural Architecture"
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* [http://www.engadget.com/2019/03/22/mit-ai-automated-neural-network-design/ MIT’s AI can train neural networks faster than ever before | Christine Fisher - Engadget] | * [http://www.engadget.com/2019/03/22/mit-ai-automated-neural-network-design/ MIT’s AI can train neural networks faster than ever before | Christine Fisher - Engadget] | ||
* [[Other codeless options, Code Generators, Drag n' Drop]] | * [[Other codeless options, Code Generators, Drag n' Drop]] | ||
| − | * [[Automated | + | * [[Algorithm Administration#Automated Learning|Automated Learning]] |
* [[Auto Keras]] | * [[Auto Keras]] | ||
* [[Evolutionary Computation / Genetic Algorithms]] | * [[Evolutionary Computation / Genetic Algorithms]] | ||
Revision as of 20:05, 27 September 2020
YouTube search... ...Google search
- Hierarchical Temporal Memory (HTM)
- MIT’s AI can train neural networks faster than ever before | Christine Fisher - Engadget
- Other codeless options, Code Generators, Drag n' Drop
- Automated Learning
- Auto Keras
- Evolutionary Computation / Genetic Algorithms
- Hyperparameters Optimization
Neural Architecture Search (NAS)
YouTube search... ...Google search
- Literature on Neural Architecture Search | AutoML.org
- Awesome NAS; a curated list
- Neural Architecture Search (NAS) with Reinforcement Learning | Wikipedia
- Neural Architecture Search (NAS) with Evolution | Wikipedia
- Multi-objective Neural architecture search | Wikipedia
- Neural Architecture Search for Deep Face Recognition | Ning Zhu
Various approaches to Neural Architecture Search (NAS) have designed networks that are on par or even outperform hand-designed architectures. Methods for NAS can be categorized according to the search space, search strategy and performance estimation strategy used:
- The search space defines which type of ANN can be designed and optimized in principle.
- The search strategy defines which strategy is used to find optimal ANN's within the search space.
- Obtaining the performance of an ANN is costly as this requires training the ANN first. Therefore, performance estimation strategies are used obtain less costly estimates of a model's performance. Neural Architecture Search | Wikipedia
Differentiable Neural Computer (DNC)
