mlsanityData to 7 Oct 2026

Score-based change point detection via tracking the best of infinitely many experts

arXiv 2408.14073 ↗First posted 26 Aug 2024cs.LG stat.ME stat.MLcited by 0

Not on the map. Why?

Abstract (arXiv)

We propose an algorithm for nonparametric online change point detection based on sequential score function estimation and the tracking the best expert approach. The core of the procedure is a version of the fixed share forecaster tailored to the case of infinite number of experts and quadratic loss functions. The algorithm shows promising results in numerical experiments on artificial and real-world data sets. Its performance is supported by rigorous high-probability bounds describing behaviour of the test statistic in the pre-change and post-change regimes.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 21 of its 69 references that are in the map. First posted on arXiv 26 Aug 2024.

Builds on

21 of 69 references.

References · 21

  1. 2020An Evaluation of Change Point Detection Algorithmscited by 62
  2. 2013Relative Loss Bounds for On-line Density Estimation with the Exponential Family of Distributionscited by 59
  3. 2016Improved Strongly Adaptive Online Learning using Coin Bettingcited by 48
  4. 2018The Many Faces of Exponential Weights in Online Learningcited by 33
  5. 2013A Nonparametric Approach for Multiple Change Point Analysis of Multivariate Datacited by 28
  6. 2015Scan B-Statistic for Kernel Change-Point Detectioncited by 28
  7. 2021MetaGrad: Adaptation using Multiple Learning Rates in Online Learningcited by 26
  8. 2020High-dimensional, multiscale online changepoint detectioncited by 19
  9. 2022Random Forests for Change Point Detectioncited by 14
  10. 2018Univariate Mean Change Point Detection: Penalization, CUSUM and Optimalitycited by 13
  11. 2018Real-Time Nonparametric Anomaly Detection in High-Dimensional Settingscited by 10
  12. 2019Optimal nonparametric multivariate change point detection and localizationcited by 10
9 more
  1. 2018A likelihood ratio approach to sequential change point detection for a general class of parameterscited by 8
  2. 2020Localizing Changes in High-Dimensional Regression Modelscited by 8
  3. 2020Online change-point detection with kernelscited by 7
  4. 2017Robust Sequential Change-Point Detection by Convex Optimizationcited by 5
  5. 2015Heterogeneous Change Point Inferencecited by 4
  6. 2020Sequential Changepoint Detection in Neural Networks with Checkpointscited by 4
  7. 2024Online Convex Optimisation: The Optimal Switching Regret for all Segmentations Simultaneouslycited by 4
  8. 2020Localising change points in piecewise polynomials of general degreescited by 3
  9. 2022High dimensional change-point detection: a complete graph approachcited by 2

Built on by

Not cited yet.