77 citations · 219 across the 17 of their papers we have counts for
5 papers · 1 filter
Quick Adaptive Ternary Segmentation: An Efficient Decoding Procedure For Hidden Markov Models
Alexandre Mösching, Housen Li, Axel Munk
Hidden Markov models (HMMs) are characterized by an unobservable Markov chain and an observable process -- a noisy version of the hidden chain. Decoding the original signal from th…
A Variational View on Statistical Multiscale Estimation
Markus Haltmeier, Housen Li, Axel Munk
We present a unifying view on various statistical estimation techniques including penalization, variational and thresholding methods. These estimators will be analyzed in the conte…
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…
Seeded intervals and noise level estimation in change point detection: A discussion of Fryzlewicz (2020)
Solt Kovács, Housen Li, Peter Bühlmann
In this discussion, we compare the choice of seeded intervals and that of random intervals for change point segmentation from practical, statistical and computational perspectives.…
Seeded Binary Segmentation: A general methodology for fast and optimal change point detection
Solt Kovács, Housen Li, Peter Bühlmann +1
In recent years, there has been an increasing demand on efficient algorithms for large scale change point detection problems. To this end, we propose seeded binary segmentation, an…