搜索结果: 1-14 共查到“计算数学 Data”相关记录14条 . 查询时间(0.375 秒)
Increasingly large data sets are being ingested and produced by simulations. What experience from large-scale simulation is transferable to big data applications? Conversely, what new optimal algorith...
2018科学发现高性能计算和数据科学研讨会（Workshop on HPC and Data Science for Scientific Discovery）
2018 科学发现高性能计算和数据科学 研讨会
2017/12/20
With the gradual establishment of computational science as the “third pillar of science” over the last few decades, it has been steadily moving from a supporting towards a leading role. HPC applicatio...
2018高性能计算的计算和数据密集型问题研讨会（Workshop on HPC for Computationally and Data-Intensive Problems）
2018 高性能计算的计算和数据密集型问题 研讨会
2017/12/20
Advances in machine learning, combinatorial optimization, and other types of mathematics, statistics, and computer science are increasingly being developed to address pressing problems in many discipl...
Data mining is the computational process for discovering valuable knowledge from data – the core of modern Data Science. It has enormous applications in numerous fields, including science, engineering...
2018大数据与教育国际会议（ICBDE 2018）（2018 International Conference on Big Data and Education）
2018 大数据与教育 国际会议
2017/11/24
Big Data is the ocean of information we swim in every day-vast zetabytes of data flowing from our computers, mobile devices, and machine sensors. With the right solutions, organizations can dive into ...
2017数据挖掘统计和数学工具专题会议（Special Session on Big Data and Disaster Management）
2017 数据挖掘统计和数学工具 专题会议
2017/9/21
Disasters are events that require multiple-agency responses, and resources beyond the capability of a community. Natural disasters put tremendous threats to the lives of people, in addition to economi...
2017 PKU Workshop on Computation and Big Data Analysis
2017 PKU Workshop Computation and Big Data Analysis
2017/3/28
The rapid growth of data starts to inflict a major impact in many fields such as computational mathematics, optimization, statistics, computer science, etc. Big data analysis is a new and exciting dir...
Data Recovering Problem Using a New KMF Algorithm for Annular Domain
Inverse Problem Annular Domain Laplace Equation Iterative Method Freefem
2013/1/30
This paper is interested at the Cauchy problem for Laplace!ˉ equation, which is to recover both Dirichlet and Neumann conditions on the inaccessible part of the boundary (inner part) of an annular dom...
An Improved Kriging Interpolation Technique Based on SVM and Its Recovery Experiment in Oceanic Missing Data
Least Square Support Vector Machine Kriging Interpolation Variogram SVM-Kriging
2013/1/30
In Kriging interpolation, the types of variogram model are very finite, which make the variogram very difficult to describe the spatial distributional characteristics of true data. In order to overcom...
Context-Dependent Data Envelopment Analysis with Interval Data
DEA Context-Dependent Interval Data Interval Attractiveness Interval Progress
2013/1/30
Data envelopment analysis (DEA) is a non-parametric method for evaluating the relative efficiency of decision making units (DMUs) on the basis of multiple inputs and outputs. The context-dependent DEA...
Improving random number generators by chaotic iterations. Application in data hiding
Chaotic sequences Topological chaos Pseudorandom random number generator
2010/12/28
In this paper, a new pseudo-random number generator (PRNG) based on chaotic iterations is proposed. This method also combines the digits of two XORshifts PRNGs.
Self-Consistent Stochastic Model Errors in Data Assimilation
37-XX 37-XX 37-XX 86-XX 86-08 46N55
2010/12/28
In using data assimilation to import information from observations to estimate parameters
and state variables of a model, one must assume a distribution for the noise in the measure-
ments and in th...
EFFICIENT AND ERROR-CORRECTING DATA STRUCTURES FOR MEMBERSHIP AND POLYNOMIAL EVALUATION
ERROR-CORRECTING DATA STRUCTURES POLYNOMIAL EVALUATION
2012/11/30
We construct efficient data structures that are resilient against a constant fraction of adversarial noise. Our model requires that the decoder answers most queries correctly with high probability and...
DATA PREORDERING IN GENERALIZED PAV ALGORITHM FOR MONOTONIC REGRESSION
Quadratic programming Large scale optimization Least distance problem Monotonic regression Partially ordered data set Pool-adjacent-violators algorithm
2007/12/11
Monotonic regression (MR) is a least distance problem with
monotonicity constraints induced by a partially ordered data set of
observations. In our recent publication [In Ser. {\sl Nonconvex
Optimi...