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cs.LG2026★ 35 cited
Evidence-based anomaly detection in clinical domains
Milos Hauskrecht, Michal Valko, Branislav Kveton +2
Anomaly detection methods can be very useful in identifying interesting or concerning events. In this work, we develop and examine new probabilistic anomaly detection methods that…
cs.LG2026★ 3 cited
Learning from a single labeled face and a stream of unlabeled data
Branislav Kveton, Michal Valko
Face recognition from a single image per person is a challenging problem because the training sample is extremely small. We consider a variation of this problem. In our problem, we…
cs.LG2026★ 21 cited
Conditional anomaly detection with soft harmonic functions
Michal Valko, Branislav Kveton, Hamed Valizadegan +2
In this paper, we consider the problem of conditional anomaly detection that aims to identify data instances with an unusual response or a class label. We develop a new non-paramet…