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Record W2901329060 · doi:10.48550/arxiv.1811.07233

Multivariate Bounded Variation Functions of Jordan-Wiener Type

2018· preprint· en· W2901329060 on OpenAlexaff
Alexander Brudnyi, Yu. A. Brudnyi

Bibliographic record

VenuearXiv (Cornell University) · 2018
Typepreprint
Languageen
FieldMathematics
TopicAdvanced Banach Space Theory
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMathematicsBounded variationBounded functionPure mathematicsPointwiseBanach spaceConstructiveCharacterization (materials science)Linear subspaceSeparable spaceType (biology)Function spaceBounded deformationGeneralizationVariation (astronomy)Lp spaceSpace (punctuation)Bounded operatorMathematical analysis

Abstract

fetched live from OpenAlex

We introduce and study spaces of multivariate functions of bounded variation generalizing the classical Jordan and Wiener spaces. Multivariate generalizations of the Jordan space were given by several prominent researchers but each of them preserved only some special properties of the space used further in few selected applications. Unlike this the multivariate generalization of the Jordan space presented in this paper preserves all known and reveals some previously unknown properties of the space. These, in turn, are special cases of the basic properties of the introduced spaces proved in the paper. They, in particular, include results on discontinuity sets and pointwise differentiability of the bounded variation functions and their Luzin type and $C^\infty$ approximation. Moreover, the second part of the paper presents results on Banach structure of function spaces of bounded variation, namely, atomic decomposition and constructive characterization of their predual spaces and then constructive characterization of preduals of the last ones and following from here the so-called two-stars theorems relating second duals of separable subspaces of "vanishing variation" to the (nonseparable) spaces of bounded variation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.402
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.105
GPT teacher head0.244
Teacher spread0.139 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2018
Admission routes1
Has abstractyes

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