Topics in Adversarial Machine Learning

Teams

Team assignment and topic assignment will be posted here.

1 minute

Below is the topic assignment for presentations after gathering all the topic preferences. Note that each student is assiged to (at most) two reseach topics.

Topic Assigned Students
Adversarial Examples & Robustness Evaluation Shreyash (Guest)
Robustness Certification Methods Gopal
Robust Overfitting & Mitigation Methods Xiao
Robust Generalization & Semi-Supervised Methods Somrita & Shreyash (Guest)
Indiscriminate Poisoning & Backdoor Attacks Baoshuang & Wenhao (Guest)
Targeted Poisoning Attacks & Certification Gopal
Intrinsic Limits on Adversarial Robustness Somrita
Adversarial ML Beyond Image Classification Baoshuang

For team project and final seminar paper, the course instructor will not assign you to a team. You can choose your teammate and form the team based on your interests. In principal, the team should consist of 2-3 students, but you are also allowed to write the seminar paper by yourself if you are deteremined to.