A curated list of automated deep learning related resources. Inspired by awesome-deep-vision, awesome-adversarial-machine-learning, awesome-deep-learning-papers, and awesome-architecture-search.
Please feel free to pull requests or open an issue to add papers.
Type | G | RL | EA | PD | Other |
---|---|---|---|---|---|
Explanation | gradient-based | reinforcement learning | evolutionary algorithm | performance prediction | other types |
Title | Venue | Type | Code |
---|---|---|---|
Neural Architecture Search with Reinforcement Learning | ICLR | RL | - |
Designing Neural Network Architectures using Reinforcement Learning | ICLR | RL | - |
Neural Optimizer Search with Reinforcement Learning | ICML | RL | - |
Learning Curve Prediction with Bayesian Neural Networks | ICLR | PD | - |
Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization | ICLR | PD | - |
Hyperparameter Optimization: A Spectral Approach | NeurIPS-W | Other | github |
Learning to Compose Domain-Specific Transformations for Data Augmentation | NeurIPS | - | - |
Title | Venue | Type | Code |
---|---|---|---|
Speeding up Automatic Hyperparameter Optimization of Deep Neural Networksby Extrapolation of Learning Curves | IJCAI | PD | github |
Title | Venue | Year | Code |
---|---|---|---|
Automated Machine Learning | Springer Book | 2019 | - |
Neural architecture search: A survey | JMLR | 2019 | - |
AutonoML: Towards an Integrated Framework for Autonomous Machine Learning | arXiv | 2020 | - |
Taking human out of learning applications: A survey on automated machine learning | arXiv | 2018 | - |
AutoML: A Survey of the State-of-the-Art | arXiv | 2019 | - |
A Survey on Neural Architecture Search | arXiv | 2019 | - |
A Comprehensive Survey of Neural Architecture Search: Challenges and Solutions | ACM Computing Surveys | 2021 | - |
On Hyperparameter Optimization of Machine Learning Algorithms: Theory and Practice | Neurocomputing | 2020 | github |
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