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Robert McCann

3 accepted papers

2023

ADMoE: Anomaly Detection with Mixture-of-Experts from Noisy Labels

AAAI 2023technical

Existing works on anomaly detection (AD) rely on clean labels from human annotators that are expensive to acquire in practice. In this work, we propose a method to leverage weak/noisy labels (e.g., risk scores generated by machine rules for detecting malware) that are cheaper to obtain for anomaly…

2019

Detecting Cyber Attacks Using Anomaly Detection with Explanations and Expert Feedback

ICASSP 2019accepted

Detecting cyber attacks in large computer networks is crucial for many organizations. To that purpose, different types of detectors capture the important signals resembling a security attack from individual computers and bring that to the attention of a security analyst. Unfortunately, the analyst s…

Cited by 0SourceScholar
2018

Dimensionality Reduction has Quantifiable Imperfections: Two Geometric Bounds

NeurIPS 2018poster

In this paper, we investigate Dimensionality reduction (DR) maps in an information retrieval setting from a quantitative topology point of view. In particular, we show that no DR maps can achieve perfect precision and perfect recall simultaneously. Thus a continuous DR map must have imperfect precis…