arXiv Machine Learning June 16, 2026 By Akira Tamamori

Localized Kernel Projection Outlyingness: A Two-Stage Approach for Multi-Modal Outlier Detection

Read the original on arXiv Machine Learning →

arXiv:2510. 24043v4 Announce Type: replace Abstract: This paper presents Two-Stage LKPLO, a novel multi-stage outlier detection framework that overcomes the coexisting limitations of conventional projection-based methods: their reliance on a fixed statistical metric and their assumption of a single data structure.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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