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In situ measurement of the electron drift velocity for upcoming directional Dark Matter detectors [PDF]
, 2014 Three-dimensional track reconstruction is a key issue for directional Dark Matter detection and it requires a precise knowledge of the electron drift velocity. Magboltz simulations are known to give a good evaluation of this parameter. However, large TPC
Billard, J. +11 more
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Survey of Concept Drift Handling Methods in Data Streams [PDF]
Jisuanji kexue, 2022 At present,concept drift in the nonstationary data stream presents a trend of different speeds and and different space distribution,which has brought great challenges to many fields such as data mining and machine learning.In the past two de-cades,many ...
CHEN Zhi-qiang, HAN Meng, LI Mu-hang, WU Hong-xin, ZHANG Xi-long
doaj +1 more source
Concept drift detection for streaming data [PDF]
2015 International Joint Conference on Neural Networks (IJCNN), 2015 Common statistical prediction models often require and assume stationarity in the data. However, in many practical applications, changes in the relationship of the response and predictor variables are regularly observed over time, resulting in the deterioration of the predictive performance of these models.
Wang, Heng, Abraham, Zubin
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Spin Drift in Highly Doped n-type Si [PDF]
, 2014 A quantitative estimation of spin drift velocity in highly doped n-type silicon (Si) at 8 K is presented in this letter. A local two-terminal Hanle measurement enables the detection of a modulation of spin signals from the Si as a function of an external
Ando, Yuichiro +7 more
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Regional Concept Drift Detection and Density Synchronized Drift Adaptation [PDF]
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017 In data stream mining, the emergence of new patterns or a pattern ceasing to exist is called concept drift. Concept drift makes the learning process complicated because of the inconsistency between existing data and upcoming data. Since concept drift was first proposed, numerous articles have been published to address this issue in terms of ...
Anjin Liu +3 more
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Detection & Management of Concept Drift
2006 International Conference on Machine Learning and Cybernetics, 2006 The ability to correctly detect the location and derive the contextual information where a concept begins to drift is essential in the study of domains with changing context. This paper proposes a Top-down learning method with the incorporation of a learning accuracy mechanism to efficiently detect and manage context changes within a large dataset ...
Mak, Lee-Onn, Krause, Paul
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Adaptive Quick Reduct for Feature Drift Detection [PDF]
Algorithms, 2021 Data streams are ubiquitous and related to the proliferation of low-cost mobile devices, sensors, wireless networks and the Internet of Things. While it is well known that complex phenomena are not stationary and exhibit a concept drift when observed for a sufficiently long time, relatively few studies have addressed the related problem of feature ...
Ferone A., Maratea A.
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Feature Drift in Fake News Detection: An Interpretable Analysis
Applied Sciences, 2023 In recent years, fake news detection and its characteristics have attracted a number of researchers. However, most detection algorithms are driven by data rather than theories, which causes the existing approaches to only perform well on specific ...
Chenbo Fu +5 more
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Drift-Aware Monocular Localization Based on a Pre-Constructed Dense 3D Map in Indoor Environments
ISPRS International Journal of Geo-Information, 2018 Recently, monocular localization has attracted increased attention due to its application to indoor navigation and augmented reality. In this paper, a drift-aware monocular localization system that performs global and local localization is presented ...
Guanyuan Feng +3 more
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