34 citations · 45 across the 3 of their papers we have counts for
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stat.ML2016★ 34 cited
How to Evaluate the Quality of Unsupervised Anomaly Detection Algorithms?
Nicolas Goix
When sufficient labeled data are available, classical criteria based on Receiver Operating Characteristic (ROC) or Precision-Recall (PR) curves can be used to compare the performan…
stat.ML2016
Sparse Representation of Multivariate Extremes with Applications to Anomaly Ranking
Nicolas Goix, Anne Sabourin, Stéphan Clémençon
Extremes play a special role in Anomaly Detection. Beyond inference and simulation purposes, probabilistic tools borrowed from Extreme Value Theory (EVT), such as the angular measu…
stat.ML2015★ 6 cited
On Anomaly Ranking and Excess-Mass Curves
Nicolas Goix, Anne Sabourin, Stéphan Clémençon
Learning how to rank multivariate unlabeled observations depending on their degree of abnormality/novelty is a crucial problem in a wide range of applications. In practice, it gene…