Awesome
<font size=6><center><big><b> Awesome AutoDL </b></big></center></font>
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.
<font size=5><center><b> Table of Contents </b> </center></font>
- Awesome Blogs
- Awesome AutoDL Libraies
- Awesome Benchmarks
- Deep Learning-based NAS and HPO
- Awesome Surveys
Awesome Blogs
- AutoML info and AutoML Freiburg-Hannover
- What’s the deal with Neural Architecture Search?
- Google Could AutoML and PocketFlow
- AutoML Challenge and AutoDL Challenge
- In Defense of Weight-sharing for Neural Architecture Search: an optimization perspective
Awesome AutoDL Libraies
Awesome Benchmarks
Deep Learning-based NAS and HPO
Type | G | RL | EA | PD | Other |
---|---|---|---|---|---|
Explanation | gradient-based | reinforcement learning | evolutionary algorithm | performance prediction | other types |
2021 Venues
2020 Venues
2019 Venues
2018 Venues
2017 Venues
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 | - | - |
Previous Venues
2012-2016
Title | Venue | Type | Code |
---|---|---|---|
Speeding up Automatic Hyperparameter Optimization of Deep Neural Networksby Extrapolation of Learning Curves | IJCAI | PD | github |
arXiv
Awesome Surveys
Title | Venue | Year | Code |
---|---|---|---|
A Comprehensive Survey of Neural Architecture Search: Challenges and Solutions | ACM Computing Surveys | 2021 | - |
Automated Machine Learning on Graphs: A Survey | ICLR-W | 2021 | GitHub |
On Hyperparameter Optimization of Machine Learning Algorithms: Theory and Practice | Neurocomputing | 2020 | github |
AutonoML: Towards an Integrated Framework for Autonomous Machine Learning | arXiv | 2020 | - |
Automated Machine Learning | Springer Book | 2019 | - |
Neural architecture search: A survey | JMLR | 2019 | - |
AutoML: A Survey of the State-of-the-Art | arXiv | 2019 | GitHub |
A Survey on Neural Architecture Search | arXiv | 2019 | - |
Taking human out of learning applications: A survey on automated machine learning | arXiv | 2018 | - |
IoT Data Analytics in Dynamic Environments: From An Automated Machine Learning Perspective | Engineering Applications of Artificial Intelligence | 2022 | github |