Neural Architecture
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- Automated Machine Learning (AML) - AutoML
- Evolutionary Computation / Genetic Algorithms
- Hyperparameters Optimization
- Other codeless options, Code Generators, Drag n' Drop
- MIT’s AI can train neural networks faster than ever before | Christine Fisher - Engadget
- Hierarchical Temporal Memory (HTM)
Neural Architecture Search (NAS)
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- Neural Architecture Search (NAS) with Reinforcement Learning | Wikipedia
- Neural Architecture Search (NAS) with Evolution | Wikipedia
- Multi-objective Neural architecture search | Wikipedia
- Awesome NAS; a curated list
Various approaches to 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)
