Results 11 to 20 of about 12,004,148 (322)
Distribution dependent stochastic differential equations [PDF]
Frontiers of Mathematics in China, 2021 Due to their intrinsic link with nonlinear Fokker-Planck equations and many other applications, distribution dependent stochastic differential equations (DDSDEs for short) have been intensively investigated. In this paper we summarize some recent progresses in the study of DDSDEs, which include the correspondence of weak solutions and nonlinear Fokker ...
Huang, Xing, Ren, Panpan, Wang, Feng-Yu
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Differential Location and Distribution of Hepatic Immune Cells
Cells, 2017 The liver is one of the main organs in the body, performing several metabolic and immunological functions that are indispensable to the organism. The liver is strategically positioned in the abdominal cavity between the intestine and the systemic ...
Maria Alice Freitas-Lopes +4 more
doaj +2 more sources
distinct: a novel approach to differential distribution analyses
bioRxiv, 2020 We present distinct, a general method for differential analysis of full distributions that is well suited to applications on single-cell data, such as single-cell RNA sequencing and high-dimensional flow or mass cytometry data.
Tiberi S +4 more
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Distribution-invariant differential privacy
Journal of Econometrics, 2023 Differential privacy is becoming one gold standard for protecting the privacy of publicly shared data. It has been widely used in social science, data science, public health, information technology, and the U.S. decennial census. Nevertheless, to guarantee differential privacy, existing methods may unavoidably alter the conclusion of the original data ...
Bi, Xuan, Shen, Xiaotong
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Differentially Private Distributed Frequency Estimation
IEEE Transactions on Dependable and Secure Computing, 2023 In order to remain competitive, Internet companies collect and analyse user data for the purpose of the improvement of user experiences. Frequency estimation is a widely used statistical tool, which could potentially conflict with the relevant privacy regulations.
Mengmeng Yang +4 more
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Adaptive Distributed Differential Evolution
IEEE Transactions on Cybernetics, 2020 Due to the increasing complexity of optimization problems, distributed differential evolution (DDE) has become a promising approach for global optimization. However, similar to the centralized algorithms, DDE also faces the difficulty of strategies' selection and parameters' setting.
Zhi-Hui Zhan +3 more
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Top quark inclusive differential distributions [PDF]
Physical Review D, 1995 The inclusive transverse momentum and rapidity distributions for top quark production at the Fermilab Tevatron are presented both in order $ _s^3$ in QCD and using the resummation of the leading soft gluon corrections in all orders of QCD perturbation theory. The resummed results are uniformly larger than the $O( _s^3)$ results for both distributions.
Kidonakis, N., Smith, J.
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Differentially Private Distributed Online Learning [PDF]
IEEE Transactions on Knowledge and Data Engineering, 2018 In the big data era, the generation of data presents some new characteristics, including wide distribution, high velocity, high dimensionality, and privacy concern. To address these challenges for big data analytics, we develop a privacy-preserving distributed online learning framework on the data collected from distributed data sources.
Chencheng Li +4 more
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Differential current-mode clock distribution [PDF]
2015 IEEE 58th International Midwest Symposium on Circuits and Systems (MWSCAS), 2015 In this paper, we present a differential current-mode pulsed flip-flop (DCMPFF) for low-power clock distribution using a representative 45nm CMOS technology. Experimental results show that the DCMPFF has 47% faster clock-to-output (CLK-Q) delay than a traditional voltage-mode (VM) pulsed flip-flop.
Guthaus, Matthew +3 more
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Optimal Schemes for Discrete Distribution Estimation Under Locally Differential Privacy [PDF]
IEEE Transactions on Information Theory, 2017 We consider the minimax estimation problem of a discrete distribution with support size $k$ under privacy constraints. A privatization scheme is applied to each raw sample independently, and we need to estimate the distribution of the raw samples from ...
Min Ye, A. Barg
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