Susanto Rahardja

Test-Time Learning for Outlier Detection

Jiawei Yang, Jingdong Chen, Susanto Rahardja

TL;DR: This work proposes a method called Local Augment (LA), designed to improve the performance of trained outlier detectors at the prediction stage without altering the trained models or accessing the training data.

In this work, the concept of test-time learning is presented, wherein Machine-Learning (ML) models are constructed by involving unlabeled test samples. Based on this concept, we propose a method called Local Augment (LA) designed to improve the performance of trained outlier dete…Read more