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Changepoints are abrupt variations in the underlying distribution of data. Detecting changes in a data stream is an important problem with many applications. In this paper, we are interested in changepoint detection algorithms which operate…

Machine Learning · Computer Science 2022-01-12 Zhaohui Wang , Xiao Lin , Abhinav Mishra , Ram Sriharsha

To develop software with optimal performance, even small performance changes need to be identified. Identifying performance changes is challenging since the performance of software is influenced by non-deterministic factors. Therefore, not…

Software Engineering · Computer Science 2023-03-28 David Georg Reichelt , Stefan Kühne , Wilhelm Hasselbring

We consider here the identification of change-points on large-scale data streams. The objective is to find the most efficient way of combining information across data stream so that detection is possible under the smallest detectable change…

Statistics Theory · Mathematics 2022-03-29 Shouri Hu , Jingyan Huang , Hao Chen , Hock Peng Chan

We argue for supplementing the process of training a prediction algorithm by setting up a scheme for detecting the moment when the distribution of the data changes and the algorithm needs to be retrained. Our proposed schemes are based on…

Machine Learning · Computer Science 2021-02-23 Vladimir Vovk , Ivan Petej , Ilia Nouretdinov , Ernst Ahlberg , Lars Carlsson , Alex Gammerman

We study the parametric online changepoint detection problem, where the underlying distribution of the streaming data changes from a known distribution to an alternative that is of a known parametric form but with unknown parameters. We…

Statistics Theory · Mathematics 2023-05-22 Liyan Xie , George V. Moustakides , Yao Xie

We investigate the online detection of changepoints in the distribution of a sequence of observations using degenerate U-statistic-type processes. We study weighted versions of: an ordinary, CUSUM-type scheme, a Page-CUSUM-type scheme, and…

Statistics Theory · Mathematics 2025-10-28 Cooper Boniece , Lajos Horvath , Lorenzo Trapani

This work develops techniques for the sequential detection and location estimation of transient changes in the volatility (standard deviation) of time series data. In particular, we introduce a class of change detection algorithms based on…

Systems and Control · Computer Science 2017-12-29 Alireza Ahrabian , Nazli Farajidavar , Clive Cheong-Took , Payam Barnaghi

We introduce a novel Bayesian method that can detect multiple structural breaks in the mean and variance of a length $T$ time-series. Our method quantifies uncertainty by returning $\alpha$-level credible sets around the estimated locations…

Methodology · Statistics 2025-07-14 Davis Berlind , Lorenzo Cappello , Oscar Hernan Madrid Padilla

Identifying players in video is a foundational step in computer vision-based sports analytics. Obtaining player identities is essential for analyzing the game and is used in downstream tasks such as game event recognition. Transformers are…

Computer Vision and Pattern Recognition · Computer Science 2022-05-02 Kanav Vats , William McNally , Pascale Walters , David A. Clausi , John S. Zelek

We adopt the interpretability offered by a parametric, Hawkes-process-inspired conditional probability mass function for the marks and apply variational inference techniques to derive a general and scalable inferential framework for marked…

Machine Learning · Statistics 2023-02-21 Aristeidis Panos , Ioannis Kosmidis , Petros Dellaportas

Baseball consists of two teams alternating between batting and fielding while competing to score runs through sequential pitching events. Recent advances in tracking technology have enabled all Major League Baseball (MLB) clubs to record…

Physics and Society · Physics 2026-04-01 Youngjai Park , Cheawoon Lim , Seung-Woo Son , Mi Jin Lee

The increasing volume of data streams poses significant computational challenges for detecting changepoints online. Likelihood-based methods are effective, but a naive sequential implementation becomes impractical online due to high…

Computation · Statistics 2025-08-08 Liudmila Pishchagina , Gaetano Romano , Paul Fearnhead , Vincent Runge , Guillem Rigaill

In this paper, we present a change point detection method for detecting change points in multivariate nonstationary wind speed time series. The change point method identifies changes in the covariance structure and decomposes the…

Methodology · Statistics 2021-05-25 Sakitha Ariyarathne , Harsha Gangammanavar , Raanju R. Sundararajan

The pattern of state changes in a biomedical time series can be related to health or disease. This work presents a principled approach for selecting a changepoint detection algorithm for a specific task, such as disease classification.…

Machine Learning · Computer Science 2024-04-22 Ayse Cakmak , Erik Reinertsen , Shamim Nemati , Gari D. Clifford

Changepoint detection is a technique used to identify significant shifts in sequences and is widely used in fields such as finance, genomics, and medicine. To identify the changepoints, dynamic programming (DP) algorithms, particularly…

Machine Learning · Statistics 2025-07-29 Tung L Nguyen , Toby Dylan Hocking

We introduce a novel geometry-oriented methodology, based on the emerging tools of topological data analysis, into the change point detection framework. The key rationale is that change points are likely to be associated with changes in…

Machine Learning · Statistics 2019-10-30 Umar Islambekov , Monisha Yuvaraj , Yulia R. Gel

Change point analysis has applications in a wide variety of fields. The general problem concerns the inference of a change in distribution for a set of time-ordered observations. Sequential detection is an online version in which new data…

Methodology · Statistics 2013-10-16 David S. Matteson , Nicholas A. James

In sports, an aging curve depicts the relationship between average performance and age in athletes' careers. This paper investigates the aging curves for offensive players in Major League Baseball. We study this problem in a missing data…

Applications · Statistics 2024-03-12 Quang Nguyen , Gregory J. Matthews

This paper addresses the problem of change-point detection on sequences of high-dimensional and heterogeneous observations, which also possess a periodic temporal structure. Due to the dimensionality problem, when the time between…

Machine Learning · Statistics 2019-03-25 Pablo Moreno-Muñoz , David Ramírez , Antonio Artés-Rodríguez

Educational assessments are valuable tools for measuring student knowledge and skills, but their validity can be compromised when test takers exhibit changes in response behavior due to factors such as time pressure. To address this issue,…

Methodology · Statistics 2025-05-06 Gabriel Wallin , Yunxiao Chen , Yi-Hsuan Lee , Xiaoou Li