Hong Kong, ICONIP’06, October 3

Alex Smola, RSISE, Machine Learning Group, Australian National University, Canberra

Prerequisites

Nothing beyond undergraduate knowledge in mathematics is expected. More specifically, I assume:

  • Basic linear algebra (matrix inverse, eigenvector, eigenvalue, etc.)
  • Some numerical mathematics (beenficial but not required), such as matrix factorization, conditioning, etc.
  • Basic statistics and probability theory (Normal distribution, conditional distributions).