Machine Learning

Topics may include but are not confined to:

• Learning via uniform convergence
• The bias-complexity trade-off
• The VC-dimension
• Model selection and validation
• Convex learning problems
• Regularization and stability
• Stochastic gradient descent
• Support vector machines
• Kernel methods
• Dimension reduction
• Bandit problems
• Manifold learning
• Reinforcement learning

One of the references will be the following textbook :

http://www.cs.huji.ac.il/~shais/UnderstandingMachineLearning/toc.html