An adaptive bandit algorithm for multiple change-point localization achieves non-asymptotic sample bounds jointly controlled by jump magnitudes and change-point spacing for any fixed δ and η.
Journal of the Royal Statistical Society Series B: Statistical Methodology , volume=
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A Group Fused LASSO plus LASSO approach with adaptive weights detects change points in piecewise-constant sparse covariance matrices and yields consistent estimators under stated conditions.
citing papers explorer
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The Sample Complexity of Multiple Change Point Identification under Bandit Feedback
An adaptive bandit algorithm for multiple change-point localization achieves non-asymptotic sample bounds jointly controlled by jump magnitudes and change-point spacing for any fixed δ and η.
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Change-point detection in variance-covariance matrix
A Group Fused LASSO plus LASSO approach with adaptive weights detects change points in piecewise-constant sparse covariance matrices and yields consistent estimators under stated conditions.