Optimization Methods for Machine Learning


Optimization techniques are used in all kinds of machine learning problems. This course gives an overview of many concepts, techniques, and optimization algorithms in machine learning and statistical pattern recognition. We also touch theory behind these methods (e.g., optimality conditions and duality theory). We also discuss how to choose and to set up the right optimization methods for different machine learning applications.

Teacher: Laura Palagi

Assistant: Umberto Dellepiane (office hours: friday 2:30-4:30 pm on email appointment)

Topics include:

  1. basics of learning theory (error functions; VC theory; margins).
  2. Supervised learning:
    • neural networks
    • support vector machines
  3. Use of standard software is discussed (WEKALIBSVM)