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1. The true sample complexity of active learning

2. Practical Bayesian Optimization of Machine Learning Algorithms

3. Meta reinforcement learning as task inference

4. Accurate Uncertainties for Deep Learning Using Calibrated Regression

5. Learning to Optimize Neural Nets

6. A Tutorial on Thompson Sampling

7. Bayesian Reinforcement Learning: A Survey

8. Wikipedia Bibliography:

   1. Active learning (machine learning)

   2. Sequential analysis

   3. https://en.wikipedia.org/wiki/Statistical_learning_theory  :

      https://en.wikipedia.org/wiki/Statistical_learning_theory