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09/18/2023
A Change-Point Approach to Estimating the Proportion of False Null Hypotheses in Multiple Testing
For estimating the proportion of false null hypotheses in multiple testi...
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07/07/2023
Fast and Optimal Inference for Change Points in Piecewise Polynomials via Differencing
We consider the problem of uncertainty quantification in change point re...
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11/08/2022
Doubly Inhomogeneous Reinforcement Learning
This paper studies reinforcement learning (RL) in doubly inhomogeneous e...
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11/07/2022
Automatic Change-Point Detection in Time Series via Deep Learning
Detecting change-points in data is challenging because of the range of p...
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10/13/2022
Detecting A Single Change-point
This chapter overviews some of the work on detecting and estimating the ...
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03/03/2022
Reinforcement Learning in Possibly Nonstationary Environments
We consider reinforcement learning (RL) methods in offline nonstationary...
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09/06/2021
Robust Narrowest Significance Pursuit: inference for multiple change-points in the median
We propose Robust Narrowest Significance Pursuit (RNSP), a methodology f...
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11/27/2020
Multiple change point detection under serial dependence: Wild energy maximisation and gappy Schwarz criterion
We propose a methodology for detecting multiple change points in the mea...
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09/11/2020
Narrowest Significance Pursuit: inference for multiple change-points in linear models
We propose Narrowest Significance Pursuit (NSP), a general and flexible ...
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03/05/2020
Exploiting disagreement between high-dimensional variable selectors for uncertainty visualization
We propose Combined Selection and Uncertainty Visualizer (CSUV), which e...
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06/05/2019
Detecting linear trend changes and point anomalies in data sequences
We propose TrendSegment, a methodology for detecting multiple change-poi...
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01/30/2019
Detecting multiple generalized change-points by isolating single ones
We introduce a new approach, called Isolate-Detect (ID), for the consist...
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12/17/2018