Sem: Adversarial Methods | Computer Science

Spring 2022

Seminar in Computer Science: Adversarial Methods

Listed in: Computer Science, as COSC-454

Faculty

Description

Artificial Intelligence (AI) and Machine Learning (ML) have enabled the broad success of automated decision making systems, but they have also created security vulnerabilities. Real and synthetic adversaries improve these AI and ML systems, advancing the state of the art in automated speech processing, image generation, computer security, and many other fields. In this course we will discuss research on the use of adversarial methods in AI, ML, and Security.

Requisite: At least one of COSC 241, 247, or 383. Limited to 20 students. Preference given to Computer Science majors. Spring 2022. Professor Alfeld.

Expectations

Students who enroll in this course will likely encounter and be expected to engage in the following intellectual skills, modes of learning, and assessment: Emphasis on readings, discussion, programming projects and analysis. Students with documented disabilities who will require accommodations in this course should be in consultation with Accessibility Services and reach out to the faculty member as soon as possible to ensure that accommodations can be made in a timely manner.

If Overenrolled: Preference given to Computer Science majors.

Offerings

2022-23: Not offered
Other years: Offered in Spring 2022

Section Navigation

Spring 2022

Seminar in Computer Science: Adversarial Methods

Faculty

Description

Offerings