Machine Learning

CS760, Spring 2020
Department of Computer Sciences
University of Wisconsin–Madison


Homework Problem Sets

There will be about 7-8 problem sets during the semester. Problem sets will consist of both written exercises and programming problems. Solutions should be submitted on Canvas. Deadlines will be posted on Canvas; those on the Schedule webpage are tentative.

Exam

  • Midterm Exam #1: Mar 9. 2:30pm-3:30pm, Soc Sci 6104.
    Topics covered: all topics in lectures up to the exam; related slides and notes (unless specified otherwise).
  • Midterm Exam #2: April 28 9am-April 29 9am. Take-home exam.
    Topics covered: all topics in lectures after Midterm Exam #1; related slides and notes (unless specified otherwise).

Midterm Exam #1 is closed book. Bring a calculator and copious amount of blank scratch paper. One 8.5x11 sheet of paper with notes on both sides allowed (handwritten or typed). Lectures and readings on the syllabus page are required, with a few exceptions (e.g., the optional readings). You are responsible for topics covered in lecture even if there are no lecture notes on the topic. You should have knowledge sufficient to work through simple examples. Exam grading questions must be raised with the instructor within one week after it is returned. Midterm Exam #2 is a take-home exam. It is open book, but each student should finish it alone (honor code). We will post the questions on Canvas at 9am CT April 28. Please submit the solution on Canvas by 9am CT April 29. The exam problem format is similar to Midterm Exam #1.

Academic Integrity

All examinations, programming assignments, and written homeworks must be done individually. Cheating and plagiarism will be dealt with in accordance with University procedures (see the UW-Madison Academic Misconduct Rules and Procedures). Hence, for example, code for programming assignments must not be developed in groups, nor should code be shared. You are encouraged to discuss with your peers, the TA or the instructors ideas, approaches and techniques broadly, but not at a level of detail where specific implementation issues are described by anyone. If you have any questions on this, ask the instructor before you act.

Exam Examples

Exams format: closed book, an A4 cheat sheet allowed. Note that the example exams below contain problems about contents that are NOT covered in this course. Such problems will NOT appear in our final exam.

Final Project

Here are some examples of research topics from a previous semester.

Students form groups of size 2-5, and submit their project proposal to the TA by email before the proposal deadline. The project proposal should include names of the students in the group, the research topic, a brief description of tentative plan for the project.

The project report will be due (pdf report and submission of any code written) to the TA by email, by the project deadline. Late days cannot be used for the project because it needs time to grade them all by the end of the exam week, in order to compute final grades on time. Grading policy will be based on the final project report and the details can be found on the About webpage.

Deadlines will be posted on Canvas; those on the Schedule webpage are tentative.