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Adaptive Matching of High-Frequency Infrared Sea Surface Images Using a Phase-Consistency Model. [PDF]
Sensors (Basel)Li X, Chen J, Li J, Yu Z, Zhang Y.
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Strong and Efficient Consistency with Consistency-aware Durability
ACM Transactions on Storage, 2021We introduce consistency-aware durability or C ad , a new approach to durability in distributed storage that enables strong consistency while delivering high performance. We demonstrate the efficacy of this approach by designing cross-client monotonic reads , a novel ...
Aishwarya Ganesan +3 more
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Strong consistency of the general rank estimator
Communications in Statistics - Theory and Methods, 2016ABSTRACTIn this article, we consider a general regression model. We are concerned with the study of the rank estimator of the regression coefficients. Strong consistency of the resulting estimator is established under mild conditions.
H. Bindele
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Weak-to-Strong Consistency Learning for Semisupervised Image Segmentation
IEEE Transactions on Geoscience and Remote Sensing, 2023Supervised remote sensing (RS) image segmentation has achieved remarkable success with large amounts of manually labeled data, which may be difficult to acquire in some practical application scenarios. Semisupervised RS image segmentation can efficiently
Xiaoqiang Lu +7 more
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Cost-Effective Strong Consistency on Scalable Geo-Diverse Data Replicas
IEEE Transactions on Cloud Computing, 2023The Raft algorithm maintains strong consistency across data replicas in Cloud. This algorithm places nodes, i.e., leader and follower, to serve read/write requests spanning geo-diverse sites.
Yu Du +5 more
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Multivariate wavelet estimators for weakly dependent processes: strong consistency rate
Communications in Statistics - Theory and Methods, 2022The present article focuses on the non parametric estimation of multivariate density and regression functions. We consider the non parametric linear wavelet-based estimators and investigate the strong consistency from the theoretical viewpoint.
Soumaya Allaoui +2 more
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2019 International Conference on Computer Science, Information Technology, and Electrical Engineering (ICOMITEE), 2019
Secret sharing is a cryptographic primitive used to securely distribute a secret value S among n participants such that only predetermined subsets of these participants (called access sets) can later reconstruct S. Such a scheme is said to be secure in the information theoretic setting if an adversary with unlimited computational power cannot reduce ...
Louis Cianciullo +3 more
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Secret sharing is a cryptographic primitive used to securely distribute a secret value S among n participants such that only predetermined subsets of these participants (called access sets) can later reconstruct S. Such a scheme is said to be secure in the information theoretic setting if an adversary with unlimited computational power cannot reduce ...
Louis Cianciullo +3 more
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Journal of nonparametric statistics (Print), 2018
In this paper we present a new estimator of the conditional density and mode when the co-variables are of functional kind. This estimator is a combination of both, the k-Nearest Neighbours procedure and the functional local linear estimation.
Z. Chikr-Elmezouar +3 more
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In this paper we present a new estimator of the conditional density and mode when the co-variables are of functional kind. This estimator is a combination of both, the k-Nearest Neighbours procedure and the functional local linear estimation.
Z. Chikr-Elmezouar +3 more
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On the strong consistency of feature‐weighted k‐means clustering in a nearmetric space
Stat, 2019Weighted k‐means (WK‐means) is a well‐known method for automated feature weight learning in a conventional k‐means clustering framework. In this paper, we analytically explore the strong consistency of the WK‐means algorithm under independent and ...
Saptarshi Chakraborty, Swagatam Das
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Strong Consistency in Nonlinear Regression
Econometric Theory, 1990Sufficient conditions are given to ensure the existence of a sequence of strongly consistent estimators of an unknown parameter for a nonlinear regression model. The parameter space includes all separable metric spaces but is not assumed to be compact.
Richardson, G. D., Bhattacharyya, B. B.
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