The material for this course will be based on previous years, when the
course was taught by Godfried Toussaint. Please follow this link to get
more information.
previous cs644 .
Please note that only the course material from the above link is relevant.
I have asked the library to place these books on reserve,
for optional reading (it is not necessary to buy them, since the course will be based on web material almost exclusively):
Richard O. Duda and Peter E. Hart and David G. Stork, Pattern Classification
Nils J. Nilsson, The Mathematical Foundations of Learning Machines
David J. Marchette, Random Graphs for Statistical Pattern Recognition
Grading scheme
Nobody complained about the tentative scheme, so here it is:

Two inclass exams (75 minutes each) worth 20% each. Most likely the first
exam will be on the 2nd of February. The second exam will be on
the last day before presentations begin (depends on class size)

One Web project , which is to be a tutorial of a topic in pattern
recognition. This consists of an HTML document worth 20%
and a JAVA applet worth 15% (due at the end of the term). You are not
expected to do original research here, just create a tutorial like the
ones used as reading material.

One oral presentation of a journal paper concerned with an
application of pattern recognition theory (20%). You are expected to
browse through pattern recognition journals to find a topic.
I am also open to substituting a journal paper presentation with a
minilecture. I imagine that this will be an introduction to a
specialized topic. For example, when I took Operations Research (now
called Discrete Optimization I),
instead of presenting a journal paper I gave an introduction to stochastic
linear programming. I expect you to propose a topic. Something related
to your field of research might be suitable.
 One brief (approx.5 minute) oral exam (held privately)
on the last day of classes (5%)