9 citations · 17 across the 4 of their papers we have counts for
4 papers
SPADE: Semi-supervised Anomaly Detection under Distribution Mismatch
Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li +2
Semi-supervised anomaly detection is a common problem, as often the datasets containing anomalies are partially labeled. We propose a canonical framework: Semi-supervised Pseudo-la…
Provable Membership Inference Privacy
Zachary Izzo, Jinsung Yoon, Sercan O. Arik +1
In applications involving sensitive data, such as finance and healthcare, the necessity for preserving data privacy can be a significant barrier to machine learning model developme…
Self-Supervised Learning with an Information Maximization Criterion
Serdar Ozsoy, Shadi Hamdan, Sercan Ö. Arik +2
Self-supervised learning allows AI systems to learn effective representations from large amounts of data using tasks that do not require costly labeling. Mode collapse, i.e., the m…
Supervised classification-based stock prediction and portfolio optimization
Sercan Arik, Sukru Burc Eryilmaz, Adam Goldberg
As the number of publicly traded companies as well as the amount of their financial data grows rapidly, it is highly desired to have tracking, analysis, and eventually stock select…