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A pruned dynamic programming algorithm to recover the best segmentations
  with $1$ to $K_{max}$ change-points
v1v2 (latest)

A pruned dynamic programming algorithm to recover the best segmentations with 111 to KmaxK_{max}Kmax​ change-points

6 April 2010
G. Rigaill
ArXiv (abs)PDFHTML

Papers citing "A pruned dynamic programming algorithm to recover the best segmentations with $1$ to $K_{max}$ change-points"

27 / 27 papers shown
Sequential Gradient Descent and Quasi-Newton's Method for Change-Point
  Analysis
Sequential Gradient Descent and Quasi-Newton's Method for Change-Point AnalysisInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Xianyang Zhang
Trisha Dawn
284
3
0
21 Oct 2022
A Semiparametric Approach to the Detection of Change-points in
  Volatility Dynamics of Financial Data
A Semiparametric Approach to the Detection of Change-points in Volatility Dynamics of Financial DataCommunications in statistics. Simulation and computation (Commun. Stat. - Simul. Comput.), 2022
Huaiyu Hu
A. Gangopadhyay
126
2
0
20 Oct 2022
Valid and Exact Statistical Inference for Multi-dimensional Multiple
  Change-Points by Selective Inference
Valid and Exact Statistical Inference for Multi-dimensional Multiple Change-Points by Selective Inference
Ryota Sugiyama
Hiroki Toda
Vo Nguyen Le Duy
Yu Inatsu
Ichiro Takeuchi
194
15
0
18 Oct 2021
Sequential (Quickest) Change Detection: Classical Results and New
  Directions
Sequential (Quickest) Change Detection: Classical Results and New DirectionsIEEE Journal on Selected Areas in Information Theory (JSAIT), 2021
Liyan Xie
Shaofeng Zou
Yao Xie
Venugopal V. Veeravalli
AI4TS
262
136
0
09 Apr 2021
A review on minimax rates in change point detection and localisation
A review on minimax rates in change point detection and localisation
Yi Yu
337
18
0
03 Nov 2020
Optimal Change-Point Detection and Localization
Optimal Change-Point Detection and Localization
Nicolas Verzélen
M. Fromont
M. Lerasle
Patricia Reynaud-Bouret
403
63
0
22 Oct 2020
Healthcare Cost Prediction: Leveraging Fine-grain Temporal Patterns
Healthcare Cost Prediction: Leveraging Fine-grain Temporal PatternsJournal of Biomedical Informatics (JBI), 2019
M. Morid
O. R. Sheng
Kensaku Kawamoto
Travis Ault
J. Dorius
S. Abdelrahman
129
32
0
14 Sep 2020
Localizing Changes in High-Dimensional Vector Autoregressive Processes
Localizing Changes in High-Dimensional Vector Autoregressive Processes
Daren Wang
Yi Yu
Alessandro Rinaldo
Rebecca Willett
383
24
0
12 Sep 2019
Optimal nonparametric change point detection and localization
Optimal nonparametric change point detection and localization
Oscar Hernan Madrid Padilla
Yi Yu
Daren Wang
Alessandro Rinaldo
271
24
0
24 May 2019
Univariate Mean Change Point Detection: Penalization, CUSUM and
  Optimality
Univariate Mean Change Point Detection: Penalization, CUSUM and Optimality
Daren Wang
Yi Yu
Alessandro Rinaldo
394
95
0
22 Oct 2018
New efficient algorithms for multiple change-point detection with
  kernels
New efficient algorithms for multiple change-point detection with kernels
Alain Celisse
G. Marot
Morgane Pierre-Jean
G. Rigaill
271
14
0
12 Oct 2017
A log-linear time algorithm for constrained changepoint detection
A log-linear time algorithm for constrained changepoint detection
T. Hocking
G. Rigaill
Paul Fearnhead
G. Bourque
OOD
275
16
0
09 Mar 2017
Changepoint Detection in the Presence of Outliers
Changepoint Detection in the Presence of Outliers
Paul Fearnhead
G. Rigaill
295
153
0
23 Sep 2016
A robust approach for estimating change-points in the mean of an AR(p)
  process
A robust approach for estimating change-points in the mean of an AR(p) process
S. Chakar
96
4
0
02 Sep 2015
A breakpoint detection error function for segmentation model selection
  and evaluation
A breakpoint detection error function for segmentation model selection and evaluation
T. Hocking
221
0
0
01 Sep 2015
Optimal change point detection in Gaussian processes
Optimal change point detection in Gaussian processes
Hossein Keshavarz
Clayton Scott
X. Nguyen
281
36
0
03 Jun 2015
Detecting structural breaks in seasonal time series by regularized
  optimization
Detecting structural breaks in seasonal time series by regularized optimization
B. Wang
Jie Sun
A. Motter
AI4TS
129
6
0
16 May 2015
Model selection for the segmentation of multiparameter exponential
  family distributions
Model selection for the segmentation of multiparameter exponential family distributions
A. Cleynen
Émilie Lebarbier
379
9
0
20 Dec 2014
Wild binary segmentation for multiple change-point detection
Wild binary segmentation for multiple change-point detection
Piotr Fryzlewicz
479
731
0
04 Nov 2014
On Optimal Multiple Changepoint Algorithms for Large Data
On Optimal Multiple Changepoint Algorithms for Large DataStatistics and computing (Stat Comput), 2014
R. Maidstone
T. Hocking
G. Rigaill
Paul Fearnhead
324
206
0
05 Sep 2014
Nonparametric maximum likelihood approach to multiple change-point
  problems
Nonparametric maximum likelihood approach to multiple change-point problems
Changliang Zou
G. Yin
Long Feng
Zhaojun Wang
285
160
0
28 May 2014
A robust approach for estimating change-points in the mean of an AR(1)
  process
A robust approach for estimating change-points in the mean of an AR(1) process
S. Chakar
Émilie Lebarbier
Céline Lévy-Leduc
Stephane S. Robin
332
4
0
08 Mar 2014
Large-Margin Metric Learning for Partitioning Problems
Large-Margin Metric Learning for Partitioning Problems
Rémi Lajugie
Sylvain Arlot
Francis R. Bach
294
8
0
06 Mar 2013
Multiscale Change-Point Inference
Multiscale Change-Point Inference
K. Frick
Axel Munk
H. Sieling
668
363
0
30 Jan 2013
Segmentation of the Poisson and negative binomial rate models: a
  penalized estimator
Segmentation of the Poisson and negative binomial rate models: a penalized estimator
A. Cleynen
Émilie Lebarbier
306
26
0
11 Jan 2013
Fast estimation of the ICL criterion for change-point detection problems
  with applications to Next-Generation Sequencing data
Fast estimation of the ICL criterion for change-point detection problems with applications to Next-Generation Sequencing dataSignal Processing (SP), 2012
A. Cleynen
T. Luong
G. Rigaill
G. Nuel
228
3
0
14 Nov 2012
Segmentor3IsBack: an R package for the fast and exact segmentation of
  Seq-data
Segmentor3IsBack: an R package for the fast and exact segmentation of Seq-dataAlgorithms for Molecular Biology (AMB), 2012
A. Cleynen
Michel Koskas
Émilie Lebarbier
G. Rigaill
Stephane S. Robin
560
39
0
25 Apr 2012
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