CSE 590Y (Security Seminar), with Adversarial Deep Learning Focus

Wednesdays @ 2:30pm in CSE 203

Topic: Adversarial Machine/Deep Learning Papers from Security Conferences (USENIX Security, Oakland, EuroSP, CCS, NDSS), and Machine learning and vision conferences (ICML, ICLR, NIPS, CVPR, ICCV, ECCV, AAAI, AISTATS, etc.)


Seminar Structure:

The goal with this seminar is to introduce participants to Adv. Deep Learning who are not necessarily working in machine learning. Though this is a field that requires some mathematical maturity to understand and value the contributions of the papers, rather than requiring that background, the course will provide some basic level of background information to the participants during each session. For the first meeting, I will spend some time on explaining background ideas independently of the papers for that day. Following that initial discussion, participants will select and present papers in the general area of adversarial deep learning. For participants who are already working in this space (or in related spaces), my expectation is that you will first spend about 15 or 20 mins discussing background concepts, and then spend another 15 or 20 mins presenting the paper. This way, for those familiar with the technicalities, it will serve as a review, and for those not familiar with the technicalities, it will serve as a helpful starting point to better appreciate the paper.

Here is a list of papers you can choose from. Feel free to select your own that are not in this list. However, before presenting, please email me (Earlence) the title of the paper so that I can make sure it is within the scope of the seminar. I will update this list as I find other interesting and relevant papers.

Paper Presentation Guidelines: