Opinionated list of resources on automatizing Machine Learning (parameter search strategies, metalearning, automatic model building).
- Grid search
- Random search
- Bayesian optimization
- Pitfalls and Best Practices in Algorithm Configuration
- Efficient Benchmarking of Algorithm Configuration Procedures via Model-Based Surrogates
- Tunability: Importance of Hyperparameters of Machine Learning Algorithms by Philipp Probst, Bernd Bischl, Anne-Laure Boulesteix
- Regularized Evolution for Image Classifier Architecture Search (AmoebaNets paper)
- DARTS: Differentiable Architecture Search
- There is a good manually curated list here
- Learning to Learn by Gradient Descent by Gradient Descent
- Backprop Evolution
- Hyper Networks (Networks that generate weights for other networks)
- Auto-sklearn
- Efficient and Robust Automated Machine Learning
- TPOT
- Randal S. Olson, Ryan J. Urbanowicz, Peter C. Andrews, Nicole A. Lavender, La Creis Kidd, and Jason H. Moore (2016). Automating biomedical data science through tree-based pipeline optimization. Applications of Evolutionary Computation, pages 123-137.
- Randal S. Olson, Nathan Bartley, Ryan J. Urbanowicz, and Jason H. Moore (2016). Evaluation of a Tree-based Pipeline Optimization Tool for Automating Data Science. Proceedings of GECCO 2016, pages 485-492.
- Layered TPOT: Speeding up Tree-based Pipeline Optimization
- This arXiv search:
- Auto-WEKA: Combined Selection and Hyperparameter Optimization of Classification Algorithms
- An algorithm for discovering Lagrangians automatically from data
- (2019) Survey on Automated Machine Learning, Marc-André Zöller, Marco F. Huber
- (2019) AutoML: A Survey of the State-of-the-ArtXin He, Kaiyong Zhao, Xiaowen Chu
- There is a good manually curated list here
- Automatic Machine Learning Workshop, ICML 2018
- Automatic Machine Learning Workshop, ICML 2017 (contains links to papers and slides)
- Metalearning Workshop, NIPS 2018
- Metalearning Workshop, NIPS 2017
- AutoML 2018 challenge - PAKDD2018 https://competitions.codalab.org/competitions/17767
- Automatic Machine Learning and How to Speed it up?, Frank Hutter
- Automatic Machine Learning using Python & scikit-learn, Abhishek Thakur
- The Past, Present, and Future of Automated Machine Learning, Randy Olson
- Machine Learning for Automated Algorithm Design
- Awesome-AutoML-Papers