Results 51 to 60 of about 2,624,164 (273)

Robust sequential design for piecewise-stationary multi-armed bandit problem in the presence of outliers

Statistical Theory and Related Fields, 2021
The multi-armed bandit (MAB) problem studies the sequential decision making in the presence of uncertainty and partial feedback on rewards. Its name comes from imagining a gambler at a row of slot machines who needs to decide the best strategy on the ...
Yaping Wang, Zhicheng Peng, Riquan Zhang, Qian Xiao   +3 more
doaj   +1 more source

gfpop: An R Package for Univariate Graph-Constrained Change-Point Detection

Journal of Statistical Software, 2023
In a world with data that change rapidly and abruptly, it is important to detect those changes accurately. In this paper we describe an R package implementing a generalized version of an algorithm recently proposed by Hocking, Rigaill, Fearnhead, and ...
Vincent Runge, Toby Dylan Hocking, Gaetano Romano, Fatemeh Afghah, Paul Fearnhead, Guillem Rigaill   +5 more
doaj   +1 more source

Hierarchical Change Point Detection on Dynamic Networks

, 2017
This paper studies change point detection on networks with community structures. It proposes a framework that can detect both local and global changes in networks efficiently. Importantly, it can clearly distinguish the two types of changes.
Chakrabarti, Aniket, Parthasarathy, Srinivasan, Sivakoff, David, Wang, Yu   +3 more
core   +1 more source

European Standard Clinical Practice Guideline and EXPeRT Recommendations for the Diagnosis and Management of Gastroenteropancreatic Neuroendocrine Neoplasms in Children and Adolescents

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Pediatric gastroenteropancreatic neuroendocrine neoplasms (GEP‐NENs) are extremely rare and clinically heterogeneous. Management has largely been extrapolated from adult practice. This European Standard Clinical Practice Guideline (ESCP), developed by the EXPeRT network in collaboration with adult NEN experts, provides (adult) evidence ...
Michaela Kuhlen, Calogero Virgone, Antje Redlich, Michael Abele, Ricardo Lopez‐Almaraz, Tal Ben‐Ami, Ewa Bien, Gianni Bisogno, Maja Mazic Cesen, Andrea Ferrari, Malgorzata A. Krawczyk, Yves Reguerre, Dominik T. Schneider, Ines B. Brecht, Charlotte Rigaud, Bilgehan Yalcin, Rainer Claus, Christian Vokuhl, Constantin Lapa, Jörg Fuchs, Segolene Hescot, Thomas Walter, Julien Hadoux, Daniel Orbach   +23 more
wiley   +1 more source

Retrospective Change-Points Detection for Multidimensional Time Series of Arbitrary Nature: Model-Free Technology Based on the ϵ-Complexity Theory

Entropy, 2021
We consider a retrospective change-point detection problem for multidimensional time series of arbitrary nature (in particular, panel data). Change-points are the moments at which the changes in generating mechanism occur.
Alexandra Piryatinska, Boris Darkhovsky
doaj   +1 more source

Dynamic change-point detection using similarity networks

, 2016
From a sequence of similarity networks, with edges representing certain similarity measures between nodes, we are interested in detecting a change-point which changes the statistical property of the networks. After the change, a subset of anomalous nodes
Cao, Shanshan, Xie, Yao
core   +1 more source

Why and When Are Evidence‐Based Interventions Adopted in Paediatric Supportive Care? A Qualitative Exploration of the Determinants of Photobiomodulation Implementation

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Oral mucositis is a common and debilitating side effect of childhood cancer and stem cell transplant treatments. It affects the quality of life of children and young people (CYP) and places a strain on services. Photobiomodulation is recommended for oral mucositis prevention in international guidance but is poorly implemented in UK ...
Claudia Heggie, Kara A. Gray‐Burrows, Peter F. Day, Bob Phillips, Carl A. Thompson   +4 more
wiley   +1 more source

Dimension-agnostic change point detection

Journal of Econometrics
Change point testing for high-dimensional data has attracted a lot of attention in statistics and machine learning owing to the emergence of high-dimensional data with structural breaks from many fields. In practice, when the dimension is less than the sample size but is not small, it is often unclear whether a method that is tailored to high ...
Hanjia Gao, Runmin Wang, Xiaofeng Shao
openaire   +2 more sources

Dynamic Interpretable Change Point Detection

, 2022
Identifying change points (CPs) in a time series is crucial to guide better decision making across various fields like finance and healthcare and facilitating timely responses to potential risks or opportunities. Existing Change Point Detection (CPD) methods have a limitation in tracking changes in the joint distribution of multidimensional features ...
Garg, Kopal, Yu, Jennifer, Behrouzi, Tina, Tonekaboni, Sana, Goldenberg, Anna   +4 more
openaire   +2 more sources

Change Point Detection Based on Cluster Transition Distributions

IEEE Access
Nowadays, Anomaly Detection (AD) models are incorporated into various systems, but they will become useless if they are not updated (i.e., re-trained) to keep up with changes in their external environment.
Shoko Takahashi, Kei Takeshita, Kazuhisa Yamagishi, Akihiro Shiozu   +3 more
doaj   +1 more source