(Advanced Topics in) Machine Learning

Time : Tuesdays and Thursdays, 10:00-11:50am
Location: Shattuck Hall (1914 SW Park Ave) (SH), Room 207.

Instructors:
Todd Leen
Bronson Creek Building 150E (at OGI , #16 on the map), 503-748-1160, tleen-AT-cse.ogi.edu.
Office hours: Tuesday and Thursday, 1:00-2:00pm, or by appointment.

Melanie Mitchell
Fourth Avenue Building 120-24 (at PSU), (503) 725-2412, mm-AT-cs.pdx.edu.
Office hours: Tuesdays, 12:00-1:30pm, Thursdays, 2:00-3:30pm, or by appointment.

Teaching Assistants: To be announced.

Course Website: :
http://www.cs.pdx.edu/~mm/machine-learning-spring-2005/index.html

Prerequisites: PSU CS 410/510 "Machine Learning" or equivalent, or permission of the instructors. Undergraduate level courses in calculus, linear algebra, and probability and statistics. Facility in at least one high-level programming language.

Course objectives: : Introduce students to several areas of machine learning from an advanced standpoint, including neural networks, reinforcement learning, Bayesian methods, computational learning theory, support vector machines, and ensemble learning methods. Give students knowledge of and experience with current theoretical tools for designing, analyzing, and evaluating these machine learning methods. Provide students with experience in reading research papers. Give students experience with performing simulations, doing statistical data analysis of the results, and writing up the results of these experiments.

Readings: There will be no textbook. The assigned readings will consist of papers on the web, handouts, or readings on reserve in the library.

Reserve Readings: The following books will be on reserve in the library. Students may be assigned supplementary readings in these books. We will be adding books to this list during the quarter.

1. T. M. Mitchell, Machine Learning.

Assignments: There will be six homework assignments, consisting of written problems and computer-based projects. All assignments are due at the beginning of class on the due date specified. For assignments turned in late without prior permission, 10% will be taken off for each day late after the due date.

Exams: There will be one midterm exam and one final exam. Both will be in-class closed book exams.

Grading: Homework: 40%, Midterm: 30%, Final: 30%.

Academic integrity: PSU students will be responsible for following the PSU Student Conduct Code, and in particular, the policy concerning academic honesty. OGI students will be responsible for following the OGI guidelines for academic integrity.

Collaboration policy: Students may discuss the general concepts and principles behind an assignment with other students. In fact, they are encouraged to do this whenever possible, because it is often a valuable way to reinforce ideas, and to learn new perspectives. However, in doing assignments, each student is expected to develop, write up, and hand in an individual solution and, in doing so, develop a sufficient understanding of the problem and solution so as to be able to explain it adequately to the instructor. Under no circumstances should a student copy or consult the solution of another student, or copy a solution from any other source, including the Internet.

Students with disabilities: If you are a student with a disability in need of academic accommodations, you should register with Disability Services for Students at PSU and notify the instructor immediately to arrange for support services.