16 citations · 49 across the 6 of their papers we have counts for
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stat.ME2022★ 16 cited
Random Forests for Change Point Detection
Malte Londschien, Peter Bühlmann, Solt Kovács
We propose a novel multivariate nonparametric multiple change point detection method using classifiers. We construct a classifier log-likelihood ratio that uses class probability p…
stat.ME2020★ 2 cited
Optimistic search: Change point estimation for large-scale data via adaptive logarithmic queries
Solt Kovács, Housen Li, Lorenz Haubner +2
Change point estimation is often formulated as a search for the maximum of a gain function describing improved fits when segmenting the data. Searching through all candidates requi…