1 code implementation • IEEE Transactions on Pattern Analysis and Machine Intelligence 2021 • Wen-Yan Lin, Siying Liu, Changhao Ren, Ngai-Man Cheung, Hongdong Li, Yasuyuki Matsushita
The foundational assumption of machine learning is that the data under consideration is separable into classes; while intuitively reasonable, separability constraints have proven remarkably difficult to formulate mathematically.
Ranked #1 on Unsupervised Anomaly Detection with Specified Settings -- 10% anomaly on STL-10 (using extra training data)