CMSC 720: Foundations of Deep Learning

Instructor

Soheil Feizi, sfeizi@cs.umd.edu
Office: 4202 IRB Building

Course Assistants

Neha Mukund Kalibhat, nehamk@umd.edu
Vinu Sankar Sadasivan, vinu@umd.edu

Topics

See the main page

Note that this is a tentative list, and we may add or remove some topics as it fits.

Lectures

Lectures are on Tuesdays and Thursdays, 3:30 pm – 4:45 pm, CSI 2117. Students are strongly encouraged to attend all the lectures.

Office Hours

The instructor and the course assistant will provide weekly office hours.

• Soheil Feizi: Tuesdays 2:30 pm – 3:30 pm.

• TA office hours: TBD

Course Piazza:

Register here.

Ask TAs about the registration code.

Prerequisites

CMSC422 or equivalent; or permission of instructor. CMSC 720 is a mathematical course. Strong linear algebra, probability, and optimization background are required. Students should be familiar with basic machine learning and deep learning concepts.

We will make extensive use of the Python programming language. It is assumed that you know or will quickly learn how the program in Python. You can satisfy this requirement by completing a programming course that uses Python and object-oriented techniques.

Course requirements and grading

Exams

• We will have one final exam on Friday, May 17, 10:30 a.m. - 12:30 p.m

Homeworks

• We will have some occasional homeworks.

Project

• CMSC 720 is a project-oriented course. Projects should be based on new works, cannot be resubmissions of previous research works by the team. Each submission should have up to 3 students. Deadlines are final and won't be extended.

• Important Dates

  • Topic and team formation deadline: 2/6

  • Report submission deadline (neurips format): 4/4

  • Review period: 4/5-4/16

  • Response to reviews, final draft: 5/2

  • Review period: 5/2-5/9

Lecture Scribing

• Each student is responsible for lecture scribing in LaTeX format on Overleaf. In general, 2–3 students will be assigned to each lecture. The scribe should elaborate on parts of the lecture that have been merely skimmed over, have full mathematical details, and provide proper references.

Grading

• Scribing + HWs 10%

• Paper 35%

• Review 20%

• Final exam 35%

Accommodations and Policies

You can find UMD's course policies here.

Any student eligible for and requesting reasonable academic accommodations due to a disability is requested to provide, to the instructor in office hours, a letter of accommodation from the Office of Accessibility and Disability Services (ADS, formerly DSS) within the first TWO weeks of the semester.

Any student who needs to be excused for an absence from a single lecture, recitation, or lab due to a medically necessitated absence shall:

• Make a reasonable attempt to inform the instructor of his/her illness prior to the class.

• Upon returning to the class, present their instructor with a self-signed note attesting to the date of their illness. Each note must contain an acknowledgment by the student that the information provided is true and correct. Providing false information to University officials is prohibited under Part 10(j) of the Code of Student Conduct (V-1.00(B) University of Maryland Code of Student Conduct) and may result in disciplinary action.

If you observe religious holidays during the course, please notify course staff within the first two weeks of the semester.

Course Evaluations

Course evaluations are important and that the department and faculty take student feedback seriously. Students can go to the link to complete their evaluations.