中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
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CAS IR Grid
机构
数学与系统科学研究院 [3]
自动化研究所 [1]
软件研究所 [1]
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OAI收割 [5]
内容类型
期刊论文 [4]
会议论文 [1]
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2023 [1]
2021 [1]
2018 [1]
2017 [1]
2004 [1]
学科主题
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Augmented Industrial Data-Driven Modeling Under the Curse of Dimensionality
期刊论文
OAI收割
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 6, 页码: 1445-1461
作者:
Xiaoyu Jiang
;
Xiangyin Kong
;
Zhiqiang Ge
  |  
收藏
  |  
浏览/下载:9/0
  |  
提交时间:2023/05/29
Curse of dimensionality
data augmentation
data-driven modeling
industrial processes
machine learning
Deep Nitsche Method: Deep Ritz Method with Essential Boundary Conditions
期刊论文
OAI收割
COMMUNICATIONS IN COMPUTATIONAL PHYSICS, 2021, 卷号: 29, 期号: 5, 页码: 1365-1384
作者:
Liao, Yulei
;
Ming, Pingbing
  |  
收藏
  |  
浏览/下载:22/0
  |  
提交时间:2021/06/01
Deep Nitsche Method
Deep Ritz Method
neural network approximation
mixed boundary conditions
curse of dimensionality
Consistent test for parametric models with right-censored data using projections
期刊论文
OAI收割
COMPUTATIONAL STATISTICS & DATA ANALYSIS, 2018, 卷号: 118, 页码: 112-125
作者:
Sun, Zhihua
;
Ye, Xue
;
Sun, Liuquan
  |  
收藏
  |  
浏览/下载:29/0
  |  
提交时间:2018/07/30
Consistent test
Curse-of-dimensionality-free
Empirical process
Projection
Right-censored data
Numerical Solution to Optimal Feedback Control by Dynamic Programming Approach: A Local Approximation Algorithm
期刊论文
OAI收割
JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY, 2017, 卷号: 30, 期号: 4, 页码: 782-802
作者:
Guo Bao-Zhu
;
Wu Tao-Tao
  |  
收藏
  |  
浏览/下载:23/0
  |  
提交时间:2018/07/30
Curse of dimensionality
Hamilton-Jacobi-Bellman equation
optimal feedback control
upwind finite difference
viscosity solutions.
cluster cores-based clustering for high dimensional data
会议论文
OAI收割
4th IEEE International Conference on Data Mining, Brighton, ENGLAND, NOV 01-04,
Shen YD
;
Shen ZY
;
Zhang SM
;
Yang Q
  |  
收藏
  |  
浏览/下载:10/0
  |  
提交时间:2011/07/29
cluster cores-based clustering
clustering algorithm
curse of dimensionality
high dimensional data
semantics-based similarity measure
time complexity
computational complexity
data mining