research
∙
06/15/2023
Geometric-Based Pruning Rules For Change Point Detection in Multiple Independent Time Series
We consider the problem of detecting multiple changes in multiple indepe...
share
research
∙
03/15/2023
Ms.FPOP: An Exact and Fast Segmentation Algorithm With a Multiscale Penalty
Given a time series in R^n with a piecewise constant mean and independen...
research
∙
10/15/2021
Fast Online Changepoint Detection via Functional Pruning CUSUM statistics
Many modern applications of online changepoint detection require the abi...
research
∙
12/12/2020
Increased peak detection accuracy in over-dispersed ChIP-seq data with supervised segmentation models
Motivation: Histone modification constitutes a basic mechanism for the g...
research
∙
11/17/2020
Adjusting the adjusted Rand Index – A multinomial story
The Adjusted Rand Index (ARI) is arguably one of the most popular measur...
research
∙
05/04/2020
Detecting Abrupt Changes in the Presence of Local Fluctuations and Autocorrelated Noise
Whilst there are a plethora of algorithms for detecting changes in mean ...
research
∙
02/10/2020
gfpop: an R Package for Univariate Graph-Constrained Change-point Detection
In a world with data that change rapidly and abruptly, it is important t...
research
∙
02/05/2019
Adjacency-constrained hierarchical clustering of a band similarity matrix with application to Genomics
Motivation: Genomic data analyses such as Genome-Wide Association Studie...
research
∙
09/29/2018
Generalized Functional Pruning Optimal Partitioning (GFPOP) for Constrained Changepoint Detection in Genomic Data
We describe a new algorithm and R package for peak detection in genomic ...
research
∙
10/12/2017
New efficient algorithms for multiple change-point detection with kernels
Several statistical approaches based on reproducing kernels have been pr...
research
∙
03/09/2017
A log-linear time algorithm for constrained changepoint detection
Changepoint detection is a central problem in time series and genomic da...
research
∙
09/23/2016
