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检索条件"机构=The Department of Mathematics and Program in Applied and Computational Mathematics"
7153 条 记 录,以下是491-500 订阅
排序:
DPpack: An R Package for Differentially Private Statistical Analysis and Machine Learning
arXiv
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arXiv 2023年
作者: Giddens, Spencer Liu, Fang Department of Applied and Computational Mathematics and Statistics University of Notre Dame Notre DameIN46556 United States
Differential privacy (DP) is the state-of-the-art framework for guaranteeing privacy for individuals when releasing aggregated statistics or building statistical/machine learning models from data. We develop the open-... 详细信息
来源: 评论
Improved Deep Neural Network Performance Under Dynamic programming Mode
SSRN
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SSRN 2023年
作者: Cabello, Julia García Department of Applied Mathematics Andalusian Research Institute in Data Science and Computational Intelligence University of Granada Spain
For Deep Neural Networks (DNN), the standard gradient-based algorithms may not be efficient because of the raised computational expense resulting from the increase in the number of layers. This paper offers an alterna... 详细信息
来源: 评论
CEM-GMsFEM for Poisson equations in heterogeneous perforated domains
arXiv
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arXiv 2024年
作者: Xie, Wei Yang, Yin Chung, Eric Huang, Yunqing National Center for Applied Mathematics in Hunan Xiangtan University Hunan Xiangtan411105 China School of Mathematics and Computational Science Xiangtan University Hunan Xiangtan411105 China Department of Mathematics The Chinese University of Hong Kong Shatin Hong Kong
In this paper, we propose a novel multiscale model reduction strategy tailored to address the Poisson equation within heterogeneous perforated domains. The numerical simulation of this intricate problem is impeded by ... 详细信息
来源: 评论
Research on Computer Big Data Deep Learning Technology in Mechanical Processing  2
Research on Computer Big Data Deep Learning Technology in Me...
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2nd IEEE International Conference on Power, Electronics and Computer Applications, ICPECA 2022
作者: Xu, Yuelin Huang, Sihao Guo, Jialin Dai, Yue Zhu, Zhilin Shenzhen MSU-BIT University Department of Computational Mathematics and Cybernetics Mathematics and Applied Mathematics Guangdong Shenzhen518172 China Shenzhen MSU-BIT University Materials Science and Engineering Guangdong Shenzhen518172 China Shenzhen MSU-BIT University International Economy and Trade Guangdong Shenzhen518172 China
Aiming at the problems that traditional manufacturing and processing equipment is not closely related to data and information in the production and processing process, and the use and maintenance of equipment relies o... 详细信息
来源: 评论
Physics-Informed Machine Learning for Electricity Markets: A NYISO Case Study
IEEE Transactions on Energy Markets, Policy and Regulation
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IEEE Transactions on Energy Markets, Policy and Regulation 2024年 第1期2卷 40-51页
作者: Ferrando, Robert Pagnier, Laurent Mieth, Robert Liang, Zhirui Dvorkin, Yury Bienstock, Daniel Chertkov, Michael University of Arizona Program in Applied Mathematics and Department of Mathematics TucsonAZ85721 United States Department of Industrial and Systems Engineering at Rutgers University PiscatawayNJ08854 United States Johns Hopkins University Department of Electrical and Computer Engineering BaltimoreMD21218-2625 United States Elec. and Comp. Eng. and Ralph o'Connor Sustainable Energy Institute Department of Civil and Systems Engineering Johns Hopkins University BaltimoreMD21218-2625 United States Columbia University IEOR New YorkNY10027 United States
This article addresses the challenge of efficiently recovering exact solutions to the optimal power flow problem in real-time electricity markets. The proposed solution, named Physics-Informed Market-Aware Active Set ... 详细信息
来源: 评论
On the Granular Representation of Fuzzy Quantifier-Based Fuzzy Rough Sets
arXiv
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arXiv 2023年
作者: Theerens, Adnan Cornelis, Chris Computational Web Intelligence Department of Applied Mathematics Computer Science and Statistics Ghent University Ghent Belgium
Rough set theory is a well-known mathematical framework that can deal with inconsistent data by providing lower and upper approximations of concepts. A prominent property of these approximations is their granular repr... 详细信息
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Symmetry groups and invariant solutions of plane Poiseuille flow
arXiv
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arXiv 2024年
作者: Aghor, Pratik P. Gibson, John F. School of Earth and Atmospheric Sciences Georgia Institute of Technology United States Integrated Applied Mathematics Program Department of Mathematics & Statistics University of New Hampshire United States
Equilibrium, traveling-wave, and periodic-orbit solutions of the Navier-Stokes equations provide a promising avenue for investigating the structure, dynamics, and statistics of transitional flows. Many such invariant ... 详细信息
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Data-driven reduced-order modelling for blood flow simulations with geometry-informed snapshots
arXiv
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arXiv 2023年
作者: Ye, Dongwei Krzhizhanovskaya, Valeria Hoekstra, Alfons G. Mathematics of Imaging & AI Department of Applied Mathematics University of Twente Netherlands Computational Science Lab Informatics Institute Faculty of Science University of Amsterdam Netherlands
Parametric reduced-order modelling often serves as a surrogate method for hemodynamics simulations to improve the computational efficiency in many-query scenarios or to perform real-time simulations. However, the snap... 详细信息
来源: 评论
Estimation of Digamma Distribution Parameters for Random Sample Size
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Moscow University computational mathematics and Cybernetics 2023年 第1期47卷 23-32页
作者: Kudryavtsev, A. A. Shestakov, O. V. Department of Computational Mathematics and Cybernetics Moscow State University Moscow Russia Moscow Center for Fundamental and Applied Mathematics Moscow Russia Federal Research Center ‘‘Informatics and Control ’’ Russian Academy of Sciences Moscow Russia
In this paper asymptotic theorems are proved for estimates of the characteristic index, the scale parameter, and the shape and scale parameters for the remaining fixed parameters of the digamma distribution with a ran...
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Optimal transport reveals dynamic gene regulatory networks via gene velocity estimation
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PLoS computational Biology 2025年 第5 May期21卷 e1012476页
作者: Zhao, Wenjun Larschan, Erica Sandstede, Björn Singh, Ritambhara Division of Applied Mathematics Brown University ProvidenceRI United States Department of Mathematics University of British Columbia Vancouver Canada Department of Molecular Biology Cell Biology and Biochemistry Center for Computational Molecular Biology Brown University ProvidenceRI United States Department of Computer Science Center for Computational Molecular Biology Brown University ProvidenceRI United States
Inferring gene regulatory networks from gene expression data is an important and challenging problem in the biology community. We propose OTVelo, a methodology that takes time-stamped single-cell gene expression data ... 详细信息
来源: 评论