Grading and policies

Table of contents

1. Course grading scheme
2. Homework
3. Projects
4. Exams and quizzes
5. Exceptions
6. Unstoppable education: the show must go on!

Course grading scheme

The course grading scheme is designed to encourage students to keep up with the course content as it happen and to ensure students meet the course learning goals.

• Homework (20%): five homework assignments on problem formulation, algorithm analysis, and algorithm design
• Midterm (45%): closed book, 75 minutes, in class on 11/3.
• Quiz (15%): closed book, 5 minutes, Wednesdays at the beginning of class starting week 2.
• Project (20%): model and solve an optimization problem, tweak an optimization algorithm and report results on a benchmark, or conduct original research in optimization.

More details about each assignment follow.

Homework

Homework will be submitted on Gradescope.

Slip days. We recognize that students are balancing many priorities, and so we make accommodations to allow for late homework. Students have 9 slip days that may be used through the quarter with no grade penalty. At most 4 slip days may be used for a single assignment. For example, you could submit two homeworks 4 days late and a third 1 day late. To calculate slip days, we round up: a homework submitted 24 hours and one minute after it is due will use two slip days. Homework submitted after all your slip days are used will receive a score of 0.

Regrades. You can ask for your homework to be regraded up until two days after grades have been posted. Regrades can increase or decrease your grade. (We will regrade the whole assignment, not just a single question.)

Weights. Although some assignments are more difficult than others, we weight all assignments equally when computing your overall homework score.

Collaboration. The goal of the homework is to help you practice the skills that you’ll use later in this class and - we hope! - later in life. Homework carries weight for your grade to encourage you to spend time on it and think deeply about it. Our collaboration policy is geared to make sure you can get the help you need, and so that by the time you turn in your work you understand what it’s about, how it works, and why it’s important.

Students are allowed - and even encouraged - to collaborate on homework. However, each student must submit their own homework. We ask that you

• Give credit to the people who have helped you: please write on your homework the names of the people you worked with.
• Give credit to the other resources that have helped you: please write on your homework the textbooks, notes, web pages, or large language models you found useful.
• Write up your homework by yourself. That is, all of the text that you submit should be typed by you. Tab completion is fine (eg, using Github Copilot).

Partial credit. If you’re not able to answer a homework question, but you show us the work that you performed to think about the question and to try to understand it, you will receive partial credit.

Sharing solutions. Under no circumstance should you seek out or look at solutions to assignments given in previous years, or share or post solutions (yours or ours) to a public website.

Projects

The course project supports our course goal of developing confidence as an optimizer by designing a solution to an optimization problem. You will choose between three types of projects for this class:

• model and solve a real-world optimization problem
• implement and tweak an optimization algorithm and report results on a benchmark
• conduct original research in optimization

You will work on the project in a team of 1-3 people. (A 1-person team is only acceptable if your project is aligned with ongoing research for your PhD.) You project should be chosen in consultation with the course staff. Come chat with any of the course staff during our office hours to clear your project with us.

As part of the project, you will submit a project proposal and final report. You will submit your project reports as a pdf, which can be prepared in LaTeX or printed from a Jupyter notebook. We may also ask you to present your findings live to the course staff or to your peers.

Exams and quizzes

The course will feature one in-class 75 minute midterm exam that assesses mastery of the core course material in optimization and will mimic the format of the ICME qualifying exam in Optimization.

Quizzes will help you keep up to speed with the material. We will hold a five-minute quiz at the beginning of class each Wednesday, starting in the second week. The quizzes are meant to be easy if you pay attention in class and read the course notes. They will focus on the previous week’s material, but may also quiz important facts from earlier in the course. We will drop your lowest quiz score.

All exams and quizzes are closed-book. One page of notes, double sided, is allowed. See the Qualifying exam tab for details about ICME qualifying exam, including practice exams, and final exams from previous years.

Exceptions

Beyond the slip days and drops outlined above, extensions on assignments will be granted only with an academic accommodation letter from the Office of Accessible Education (generally for medical reasons). or in other such exceptional circumstances. Requests due to job interviews, other classes and assignments, and poor planning will not be considered. We suggest you save your slip days to insure against catastrophe.

Unstoppable education: the show must go on!

Stanford as an institution is committed to the highest quality education, and as your teaching team, our first priority is to uphold your educational experience. To that end we are committed to following the syllabus as written here, including through short or long-term disruptions, such as public health emergencies, natural disasters, or protests and demonstrations. However, there may be extenuating circumstances that necessitate some changes. Should adjustments be necessary, we will communicate clearly and promptly to ensure you understand the expectations and are positioned for successful learning.