Change-point detection in time-series data by relative density-ratio estimation

DOI10.1016/j.neunet.2013.01.012zbMath1367.62259arXiv1203.0453OpenAlexW1682770403WikidataQ30600345 ScholiaQ30600345MaRDI QIDQ2510812

Nigel Collier, Makoto Yamada, Song Liu, Masashi Sugiyama

Publication date: 4 August 2014

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1203.0453

zbMATH Keywords

kernel methodstime-series datachange-point detectiondistribution comparisonrelative density-ratio estimation

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Learning and adaptive systems in artificial intelligence (68T05)

Related Items

Unnamed Item, Data-adaptive symmetric CUSUM for sequential change detection, Density-Difference Estimation, Direct Density Derivative Estimation, Direct Learning of Sparse Changes in Markov Networks by Density Ratio Estimation, Bias Reduction and Metric Learning for Nearest-Neighbor Estimation of Kullback-Leibler Divergence, Optimal nonparametric change point analysis, Scan B-statistic for kernel change-point detection, A comprehensive and systematic look up into deep learning based object detection techniques: a review, Intrinsic Mode Function Selection and Statistical Information Analysis for Bearing Ball Fault Detection

Uses Software

• bootstrap

Cites Work

• Direct importance estimation for covariate shift adaptation
• Statistical analysis of kernel-based least-squares density-ratio estimation
• Direct density-ratio estimation with dimensionality reduction via least-squares hetero-distributional subspace search
• Estimating the dimension of a model
• Dual representation of \(\phi\)-divergences and applications.
• Dimensionality reduction for density ratio estimation in high-dimensional spaces
• Support-vector networks
• Density-ratio matching under the Bregman divergence: a unified framework of density-ratio estimation
• Computational complexity of kernel-based density-ratio estimation: a condition number analysis
• Least-squares two-sample test
• Estimating the Support of a High-Dimensional Distribution
• Density Ratio Estimation in Machine Learning
• An Algorithm Based on Singular Spectrum Analysis for Change-Point Detection
• The marginalized likelihood ratio test for detecting abrupt changes
• Sequential change‐point detection based on direct density‐ratio estimation
• $f$-Divergence Estimation and Two-Sample Homogeneity Test Under Semiparametric Density-Ratio Models
• Estimating Divergence Functionals and the Likelihood Ratio by Convex Risk Minimization
• An online kernel change detection algorithm
• On Information and Sufficiency
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item