555 citations · 1.4k across the 24 of their papers we have counts for
25 papers
Non-parametric multiple change-point detection
Andreas Anastasiou, Piotr Fryzlewicz
We introduce a methodology, labelled Non-Parametric Isolate-Detect (NPID), for the consistent estimation of the number and locations of multiple change-points in a non-parametric s…
Fast and Optimal Inference for Change Points in Piecewise Polynomials via Differencing
Shakeel Gavioli-Akilagun, Piotr Fryzlewicz
We consider the problem of uncertainty quantification in change point regressions, where the signal can be piecewise polynomial of arbitrary but fixed degree. That is we seek disjo…
Doubly Inhomogeneous Reinforcement Learning
Liyuan Hu, Mengbing Li, Chengchun Shi +2
This paper studies reinforcement learning (RL) in doubly inhomogeneous environments under temporal non-stationarity and subject heterogeneity. In a number of applications, it is co…
Automatic Change-Point Detection in Time Series via Deep Learning
Jie Li, Paul Fearnhead, Piotr Fryzlewicz +1
Detecting change-points in data is challenging because of the range of possible types of change and types of behaviour of data when there is no change. Statistically efficient meth…
Detecting A Single Change-point
Paul Fearnhead, Piotr Fryzlewicz
This chapter overviews some of the work on detecting and estimating the location of a single change. We first consider the most common change-point problem, namely that of detectin…
Testing Stationarity and Change Point Detection in Reinforcement Learning
Mengbing Li, Chengchun Shi, Zhenke Wu +1
We consider offline reinforcement learning (RL) methods in possibly nonstationary environments. Many existing RL algorithms in the literature rely on the stationarity assumption th…