CS/ECE/STAT-861: Theoretical Foundations of Machine Learning

Grading overview

• Proofreading lecture notes (slides): 4%

• Homeworks: 42%

• Take-home exam: 32%

• Course project (designing a homework problem): 22%

Auditing: Students auditing the class need to complete only the proofreading portion.

Proofreading Lecture Slides

Each student will be required to proofread the lecture notes (slides) for approximately two lectures. There will be about two students assigned per lecture. This may change if enrollment drops significantly.

Students assigned to proofreading must attend class. After class, you will carefully review the lecture notes covered during the session and identify any errors, unclear explanations, or points that could be improved. You will then email me a PDF file containing your corrections. Your submission may be marked directly on the downloaded slides or be typed up as a separate PDF.

Each student will send separate submissions and will be evaluated based on their own submission.

Corrections must be submitted within two days of the lecture. After reviewing your feedback, I will update the lecture notes posted on the course website.

If you decide to drop the class before your date, please delete your name from the sign up slot and email me. If you have enrolled, but are not sure about taking the class, please sign up for later classes (after Oct 6).

Homeworks

There will be  4 problem sets in addition to homework 0. Homeworks will be posted on Canvas and will be due by 11.59pm on the due date.

• All homeworks will not necessarily have equal credit. Longer/harder homeworks will be weighted more towards your final homework score.

• Homeworks should be typeset using some appropriate software. We will not be accepting written and scanned homeworks. You are strongly encourated to typeset your solutions using LaTeX.

• As we will re-use questions in future offerings of this class, please do not release homework solutions outside of class or discuss them in public forums.

• Collaboration: You are allowed (and encouraged) to collaborate in groups of size up to three on starred problems (indicated by a \(\star\)). However, each student must write up solutions individually and name any collaborators at the top of each problem. You may not collaborate on the remaining problems. Please read the university's policy on academic misconduct.

• Solutions will be posted within a week of the deadline. Students will receive zero credit for submissions after solutions are posted.

• Late submissions:

  • You will be allowed three (3) total late days without penalty for the entire semester. You may be late by 1 day on three different homeworks, late by 2 days on one homework and by 1 day on another, or by 3 days on a single homework.

  • Once those days are used, you will be penalized according to the following policy: Homework is worth full credit if submitted by the deadline. It is worth half credit for the next 48 hours. It is worth zero credit after that.

  • You must turn in all of the homeworks, even if for zero credit, in order to pass the course.

  • Any submission after the deadline will be counted as a late day, even if it is just a few seconds. Please plan to submit your homework well ahead of the deadline.

  • Extensions are extremely unlikely, and will be considered only for documented emergencies.

Take-home exam

The exam will be held from Monday 11/17/2025 12.01 AM – Friay 11/21/2025 11.59 PM. The length of the exam is 48 hours. Students can start the exam at a convenient time within this period, but must submit their solution by 11.59 PM on 11/24 and within 48 hours of the start time.

You may refer to any of the lecture slides or your own notes during the exam. You may not refer to any other material, search the internet, or use LLM-based tools. Unlike the homeworks, you are not allowed to collaborate or discuss the questions with other students in class. Please read the university's policy on academic misconduct.

As we will re-use problems in future offerings of this class, please do not release exam problems or solutions outside of class or discuss them in public forums.

Students will receive 5 percent extra credit if their solutions are typeset in LaTex. If you choose to submit a handwritten exam, please make sure your handwriting is legible. We will not spend undue effort trying to understand poor handwriting.

Course project

For the course project, you will work in groups of size up to three, to design a homework question. You will then have the opportunity to attempt (and evaluate) the problems designed by your peers.

• Each group should submit your problem, along with the solutions, by Saturday 11/15/2025.

• I will then randomly assign  2 of the submitted questions to each student. The solutions to these problems will be due by Saturday 12/6/2025.

• Along with the solutions, you will also submit an evaluation of the problem that you attempted.

• A preliminary draft is due by 10/8/2025. I will take this feedback into consideration when determining the grade for each problem.

Guidelines. A good homework problem should reinforce class concepts and appropriately challenge your peers. Here are some key guidelines:

• Ensure the problem has a coherent focus rather than a collection of unrelated questions.

• The problem should allow students to apply concepts learned in class, and not simply recall information.

• Ensure the problem statement is unambiguous, with clear and precise instructions on what is expected. Clearly state any assumptions or constraints.

• The problem should be challenging enough to stimulate critical/creative thinking, but not overly difficult that it becomes frustrating. Consider including parts that progressively build on each other.

• Ideally, the problem will teach the student (and the instructor!) something new. You are encouraged to design questions that explores new topics, provided that you provide necessary background knowledge/information.

If you develop an outstanding homework problem, I will consider including it in future iterations of this course and will acknowledge your contribution.

You may model the level of difficulty and depth based on the starred problems in homeworks 1–4.