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Hamid Reza Dehbashi

2 accepted papers

2024

Killing It With Zero-Shot: Adversarially Robust Novelty Detection

ICASSP 2024accepted

Novelty Detection (ND) plays a crucial role in machine learning by identifying new or unseen data during model inference. This capability is especially important for the safe and reliable operation of automated systems. Despite advances in this field, existing techniques often fail to maintain their…

Cited by 0SourceScholar
2024

RODEO: Robust Outlier Detection via Exposing Adaptive Out-of-Distribution Samples

ICML 2024poster

In recent years, there have been significant improvements in various forms of image outlier detection. However, outlier detection performance under adversarial settings lags far behind that in standard settings. This is due to the lack of effective exposure to adversarial scenarios during training,…