CSCI2952-X
Research Topics in Self Supervised Learning
Fall 2024
We will cover the core components of current self supervised learning pipelines: (i) data preprocessing, (ii) data augmentation, (iii) optimization, and (iv) fine-tuning. For each, we will read and discuss recent papers and work in group to implement our own alternative solutions.
Instructor(s): | |
Meets: | MWF 1pm-1:50pm in CIT Center (Thomas Watson CIT) 165 |
Exam: | No final exam has been scheduled for this course by the department through the registrar's office. Please consult syllabus or contact instructor. If an exam were to have scheduled, it would have been held: |
Max Seats: | 50 Full |
CRN: | 19497 |