Results 21 to 30 of about 4,387 (252)
IEEE Access, 2019 This paper considers a ℓ1-coefficient regularized regression algorithm with multiscale kernels based on non-independent and identically distributed (non-i.i.d.) samples.
Lu Liu, Bo Liu
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Automatic Road Extraction from Remote Sensing Images Based on Rectangle Marked Point Process
Canadian Journal of Remote Sensing, 2021 Aiming at solving inaccurate and incomplete extraction of road in remote sensing images, this paper proposes an automatic extraction algorithm based on Rectangle Marked Point Process (RMPP).
You Wu, Quanhua Zhao, Yu Li, Yiding Wang
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PLoS Computational Biology, 2023 Estimating the distance at which pathogens disperse from one season to the next is crucial for designing efficient control strategies for invasive plant pathogens and a major milestone in the reduction of pesticide use in agriculture.
Hola K Adrakey +4 more
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Meta-Feature Fusion for Few-Shot Time Series Classification
IEEE Access, 2023 Deep learning has been widely adopted for end-to-end time-series classification (TSC). However, the effectiveness of deep learning heavily relies on large-scale data.
Seo-Hyeong Park +2 more
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Applied Sciences, 2021 A new methodology, the hybrid learning system (HLS), based upon semi-supervised learning is proposed. HLS categorizes hyperspectral images into segmented regions with discriminative features using reduced training size.
Syed Taimoor Hussain Shah +10 more
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Positive Operator Valued Measures and Feller Markov kernels [PDF]
Journal of Mathematical Analysis and Applications, 2016 26 pages.
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Optimal measures and Markov transition kernels [PDF]
Journal of Global Optimization, 2012 We study optimal solutions to an abstract optimization problem for measures, which is a generalization of classical variational problems in information theory and statistical physics. In the classical problems, information and relative entropy are defined using the Kullback-Leibler divergence, and for this reason optimal measures belong to a one ...
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Asymptotics of Markov Kernels and the Tail Chain [PDF]
Advances in Applied Probability, 2013 An asymptotic model for the extreme behavior of certain Markov chains is the ‘tail chain’. Generally taking the form of a multiplicative random walk, it is useful in deriving extremal characteristics, such as point process limits. We place this model in a more general context, formulated in terms of extreme value theory for transition kernels, and ...
Resnick, Sidney I., Zeber, David
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Rate Functions for Symmetric Markov Processes via Heat Kernel [PDF]
Potential Analysis, 2016 By making full use of heat kernel estimates, we establish the integral tests on the zero-one laws of upper and lower bounds for the sample path ranges of symmetric Markov processes. In particular, these results concerning on upper rate bounds are applicable for local and non-local Dirichlet forms, while lower rate bounds are investigated in both ...
Shiozawa, Yuichi, Wang, Jian
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