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Abstract and Applied Analysis
Article . 2014 . Peer-reviewed
License: CC BY
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Abstract and Applied Analysis
Article
License: CC BY
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Analysis of Approximation by Linear Operators on VariableLρp(·)Spaces and Applications in Learning Theory

Authors: Bing-Zheng Li; Ding-Xuan Zhou;

Analysis of Approximation by Linear Operators on VariableLρp(·)Spaces and Applications in Learning Theory

Abstract

This paper is concerned with approximation on variableLρp(·)spaces associated with a general exponent functionpand a general bounded Borel measureρon an open subsetΩofRd. We mainly consider approximation by Bernstein type linear operators. Under an assumption of log-Hölder continuity of the exponent functionp, we verify a conjecture raised previously about the uniform boundedness of Bernstein-Durrmeyer and Bernstein-Kantorovich operators on theLρp(·)space. Quantitative estimates for the approximation are provided for high orders of approximation by linear combinations of such positive linear operators. Motivating connections to classification and quantile regression problems in learning theory are also described.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Average
Average
Average
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