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检索条件"机构=Applied Statistics and Data Science"
779 条 记 录,以下是21-30 订阅
排序:
Expressivity of deterministic quantum computation with one qubit
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Physical Review A 2025年 第2期111卷 022429-022429页
作者: Yujin Kim Daniel K. Park Department of Statistics and Data Science Yonsei University Seoul 03722 Republic of Korea Department of Applied Statistics Yonsei University Seoul 03722 Republic of Korea
Deterministic quantum computation with one qubit (DQC1) is of significant theoretical and practical interest due to its computational advantages in certain problems, despite its subuniversality with limited quantum re... 详细信息
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Exposing factors influencing Korean leisure life satisfaction through machine learning techniques
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Discover Artificial Intelligence 2024年 第1期4卷 1-15页
作者: Lee, Yong-Kwan Kim, Boohyun Kim, Jinheum Korea Culture & amp Tourism Institute Seoul07511 Korea Republic of Department of Data Science University of Suwon Hwaseong18323 Korea Republic of Department of Applied Statistics University of Suwon 17 Wauan-Gil Bongdam-Eup Hwaseong18323 Korea Republic of
This study examines factors influencing leisure life satisfaction (LLS) through machine learning techniques based on the data from the 2019 National Leisure Activity Survey in Korea. The results show that using machin... 详细信息
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Nonstationary Sparse Spectral Permanental Process  38
Nonstationary Sparse Spectral Permanental Process
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38th Conference on Neural Information Processing Systems, NeurIPS 2024
作者: Sun, Zicheng Zhang, Yixuan Ling, Zenan Fan, Xuhui Zhou, Feng Center for Applied Statistics and School of Statistics Renmin University of China China School of Statistics and Data Science Southeast University United States School of EIC Huazhong University of Science and Technology China School of Computing Macquarie University Australia Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing China
Existing permanental processes often impose constraints on kernel types or stationarity, limiting the model's expressiveness. To overcome these limitations, we propose a novel approach utilizing the sparse spectra...
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Bifurcation analysis of a diffusive radio-dependent model with spatial memory
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International Journal of Biomathematics 2024年 第8期17卷 309-347页
作者: Qi An Xingyu Guo Xuebing Zhang College of Mathematics and Statistics Nanjing University of Information Science and Technology Nanjing 210044 P.R.China Jiangsu International Joint Laboratory on System Modeling and Data Analysis Center for Applied Mathematics of Jiangsu Province Nanjing University of Information Science and Technology Nanjing 210044 P.R.China
This is an Open Access article published by World Scientific Publishing *** is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0(CC BY-NC-ND)License,which permits use,dist... 详细信息
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Automatic Discovery of Controversial Legal Judgments by an Entropy-Based Measurement  35
Automatic Discovery of Controversial Legal Judgments by an E...
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35th International Conference on Software Engineering and Knowledge Engineering, SEKE 2023
作者: Zhou, Jing Leng, Shan Wang, Fang Wang, Hansheng Center for Applied Statistics School of Statistics Renmin University of China China Department of Statistics University of Wisconsin Madison United States Data Science Institute Shandong University China Guanghua School of Management Peking University China
The judgment of controversial cases has always been an important judicial issue, but it is not easy to discover them in practice. In this paper, based on 1,361,354 legal instruments data collected from China Judgments... 详细信息
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General Frameworks for Conditional Two-Sample Testing
arXiv
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arXiv 2024年
作者: Lee, Seongchan Cha, Suman Kim, Ilmun Department of Statistics and Data Science Yonsei University Seoul Korea Republic of Department of Statistics and Data Science Department of Applied Statistics Yonsei University Seoul Korea Republic of
We study the problem of conditional two-sample testing, which aims to determine whether two populations have the same distribution after accounting for confounding factors. This problem commonly arises in various appl... 详细信息
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Computational-Statistical Trade-off in Kernel Two-Sample Testing with Random Fourier Features
arXiv
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arXiv 2024年
作者: Choi, Ikjun Kim, Ilmun Department of Statistics and Data Science Yonsei University Seoul Korea Republic of Department of Statistics and Data Science Department of Applied Statistics Yonsei University Seoul Korea Republic of
Recent years have seen a surge in methods for two-sample testing, among which the Maximum Mean Discrepancy (MMD) test has emerged as an effective tool for handling complex and high-dimensional data. Despite its succes... 详细信息
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UNDERSTANDING GENERALIZATION IN QUANTUM MACHINE LEARNING WITH MARGINS
arXiv
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arXiv 2024年
作者: Hur, Tak Park, Daniel K. Department of Statistics and Data Science Yonsei University Seoul Korea Republic of Department of Applied Statistics Department of Statistics and Data Science Yonsei University Seoul Korea Republic of
Understanding and improving generalization capabilities is crucial for both classical and quantum machine learning (QML). Recent studies have revealed shortcomings in current generalization theories, particularly thos... 详细信息
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Characterizations of Weighted Besov Spaces with Variable Exponents
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Acta Mathematica Sinica,English Series 2024年 第11期40卷 2855-2878页
作者: Sheng Rong WANG Peng Fei GUO Jing Shi XU School of Mathematics and Statistics Hainan Normal UniversityHaikou571158P.R.China Center for Applied Mathematics of Guangxi Guangxi Colleges and Universities Key Laboratory of Data Analysis and ComputationSchool of Mathematics and Computing ScienceGuilin University of Electronic TechnologyGuilin541004P.R.China
In this paper,we first give characterizations of weighted Besov spaces with variable exponents via Peetre’s maximal *** we obtain decomposition characterizations of these spaces by atom,molecule and *** an applicatio... 详细信息
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TransFeat-TPP: An Interpretable Deep Covariate Temporal Point Processes  27
TransFeat-TPP: An Interpretable Deep Covariate Temporal Poin...
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27th European Conference on Artificial Intelligence, ECAI 2024
作者: Meng, Zizhuo Li, Boyu Fan, Xuhui Li, Zhidong Wang, Yang Chen, Fang Zhou, Feng Data Science Institute University of Technology Sydney Australia School of Computing Macquarie University Australia Center for Applied Statistics School of Statistics Renmin University of China China Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing China
The classical temporal point process (TPP) constructs an intensity function by taking the occurrence times into account. Nevertheless, occurrence time may not be the only relevant factor, other contextual data, termed... 详细信息
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