CS 3750  Advanced Topics in Machine Learning (ISSP 3535)

Time:  Tuesday, Thursday 9:30 am - 10:45 am 
Location: Sennott Square, Room 5313

Instructor:  Milos Hauskrecht
Computer Science Department
5329 Sennott Square
phone: x4-8845
e-mail: milos_at_cs_pitt_edu
office hours: TBA

Topics and related readings.

Basics of Matrix algebra

Basics of density estimation Bayesian Belief networks

Complexity Results

Exact inference algorithms

Monte Carlo methods:

Loopy Belief propagation

Learning Belief networks from data



Component analysis


Applications of PCA:

EM algorithms for PCA

Latent Variable Models for text analysis, information retrieval and link analysis

Probabilistic component analysis

Variational methods


Variational ML learning for component analysis

Variational Bayesian learning:

Other variational learning papers

Kernel methods

Support vector machines (basics):

Kernel methods (basics):

Kernel PCA:

Kernel ICA:

Various kernels