Regularized Nyström Subsampling in Covariate Shift Domain Adaptation Problems

IF 1.4 4区 数学 Q2 MATHEMATICS, APPLIED
Hanna L. Myleiko, Sergei G. Solodky
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引用次数: 0

Abstract

The unsupervised domain adaptation problem with covariate shift assumption is considered. Within the framework of the Reproducing Kernel Hilbert Space concept, an algorithm is constructed that is a...
变量偏移域适应问题中的正则化尼斯特伦子采样
研究考虑了具有协变量移动假设的无监督域适应问题。在重现核希尔伯特空间概念的框架内,构建了一种算法,该算法是...
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来源期刊
CiteScore
2.40
自引率
8.30%
发文量
74
审稿时长
6-12 weeks
期刊介绍: Numerical Functional Analysis and Optimization is a journal aimed at development and applications of functional analysis and operator-theoretic methods in numerical analysis, optimization and approximation theory, control theory, signal and image processing, inverse and ill-posed problems, applied and computational harmonic analysis, operator equations, and nonlinear functional analysis. Not all high-quality papers within the union of these fields are within the scope of NFAO. Generalizations and abstractions that significantly advance their fields and reinforce the concrete by providing new insight and important results for problems arising from applications are welcome. On the other hand, technical generalizations for their own sake with window dressing about applications, or variants of known results and algorithms, are not suitable for this journal. Numerical Functional Analysis and Optimization publishes about 70 papers per year. It is our current policy to limit consideration to one submitted paper by any author/co-author per two consecutive years. Exception will be made for seminal papers.
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