The goals of this course are (1) to understand and form a perspective on the state of the art symbolic machine learning methods, (2) to refine skills in critically reading, presenting, performing, and evaluating research, and (3) to perform a substantial research project in machine learning. This class will give the opportunity to delineate and grapple with a challenging research problem of your choice through a semester-long research project.
The emphasis of the course will be on on projects, presentations, and discussion, but there will be some homework assignments to highlight important issues and techniques, possibly including short assignments given out in one class and due the next. If you have to miss a class, you are still responsible for any readings and homeworks assigned there, so be sure to check with other students to find out what material you missed.
Each student will be responsible for presentations to the class, including presenting and leading a discussion starting from a paper. Each student will also be assigned to be "discussant" for another student presentation. The discussant should be prepared to raise additional questions and issues and to respond to the main presentation and by the next class to submit a short writeup of comments on strengths and weaknesses of the presentation, suggestions for improvements, and any ideas prompted by the presentation or discussion.
The projects will give an opportunity to investigate a topic of your choice. You may form two-person groups for the projects or do them individually. Each project group is responsible for a short written project sketch, a short presentation during the semester, a presentation/discussion at the end of the course, a well-documented program and a written writeup on the program.
Homeworks will count 20%, participation as discussant will count 10%, paper presentations will count 25%, and the final project (including the project presentation) will count 45%.
Incompletes will be handled in accordance with Computer Science Department policy. In particular, incompletes will only be given to students who have successfully completed most of the coursework, and who have an acceptable reason for the incomplete.
The home page at URL http://www.cs.indiana.edu/classes/b652/index.html (also accessible from the CS home page at http://www.cs.indiana.edu) can be used to access this handout and other policy statements for the class, the class syllabus, lists of useful references, etc. Copies of each new assignment and other materials will be added as the semester progresses.
Students who need any special accommodation must contact the the professor during the first week of class to discuss arrangements.
The Computer Science department has prepared a statement on academic integrity describing the obligations of students, a copy of which is accessible from the class web page. All students must read it before beginning the first homework assignment. All work must be done independently unless collaboration is explicitly allowed, and all collaboration must be properly acknowledged. Students are responsible for asking us if they have any questions about the policies stated here and in the departmental handout.
If you have any questions that this doesn't cover (or just want to discuss something about the course or AI) please let me know!
January 6, 2007