Neural Architecture

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• 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 Machine Learning (AML) - AutoML
• Auto Keras
• Evolutionary Computation / Genetic Algorithms
• Hyperparameters Optimization

Neural Architecture Search (NAS)

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• Literature on Neural Architecture Search | AutoML.org
• Awesome NAS; a curated list
• Neural Architecture Search (NAS) with Reinforcement Learning | Wikipedia
  • Reinforcement Learning (RL)
• 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)

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