67638 ADVANCED COURSE IN MACHINE LEARNING

Teacher: Shai Shalev-Shwartz

Lecture notes:

• Lecture 1 --- Active learning and Bandits
• Lecture 2 --- Selective Sampling and QBC
• Lecture 3 --- Disagreement Coefficient and the A^2 algorithm
• Lecture 4 --- Online Convex Optimization
• Lecture 5 --- Shifting and Drifting bounds
• Lecture 6 --- Online Learning and Games
  See also this file and the Geometeric Calibration paper.
• Lecture 7 --- Online learning with parial feedback.
• Lecture 8 --- Generalization bounds: PAC-Bayes, compression, online-to-batch
• Lecture 9 --- Learnability, Stability and Uniform Convergence
• Lecture 10 --- The computataional complexity of learning
• We also talked about learning decision trees. Here is an unfinished lecture about Kuchilevitz-Mansour algorithm and here is a lecture note prepared by Shie Mannor on learning DNF formulas
• Lecture 12 --- Multiclass categorization

Additional information is given in the course website.