Papers to compare the methods with

[vivekaxl]

2011:

• [ ] (Bayesian Optimization with random forests:) Hutter, F. and Hoos, H. H. and Leyton-Brown, K. (pdf)(slides)(bib) Sequential Model-Based Optimization for General Algorithm Configuration In: Proceedings of the conference on Learning and Intelligent OptimizatioN (LION 5) http://ml.informatik.uni-freiburg.de/papers/11-LION5-SMAC.pdf

2012:

• [ ] Jasper Snoek, Hugo Larochelle, Ryan P. Adams: Practical Bayesian Optimization of Machine Learning Algorithms. NIPS 2012: 2960-2968 http://papers.nips.cc/paper/4522-practical-bayesian-optimization-of-machine-learning-algorithms

2013:

• [ ] Chris Thornton and Frank Hutter and Holger H. Hoos and Kevin Leyton-Brown Auto-WEKA: Combined Selection and Hyperparameter Optimization of Classification Algorithms In: Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'13) http://ml.informatik.uni-freiburg.de/papers/13-KDD2013-AutoWEKA.pdf

2015:

• [ ] Feurer, M. and Klein, A. and Eggensperger, K. and Springenberg, J. and Blum, M. and Hutter, F. Efficient and Robust Automated Machine Learning In: Advances in Neural Information Processing Systems 28 http://ml.informatik.uni-freiburg.de/papers/15-NIPS-auto-sklearn-preprint.pdf

2016:

• [ ] Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization Lisha Li, Kevin Jamieson, Giulia DeSalvo, Afshin Rostamizadeh, Ameet Talwalkar https://arxiv.org/pdf/1603.06560.pdf

2017:

• [ ] Neural Architecture Search with Reinforcement Learning Barret Zoph, Quoc V. Le In: International Conference on Learning Representations (ICLR) 2017 Conference Track https://arxiv.org/pdf/1611.01578.pdf

• [ ] Klein, A. and Falkner, S. and Springenberg, J. T. and Hutter, F. Learning Curve Prediction with Bayesian Neural Networks In: International Conference on Learning Representations (ICLR) 2017 Conference Track http://ml.informatik.uni-freiburg.de/papers/17-ICLR-LCNet.pdf