MétaCan
Menu
Back to cohort
Record W4290980896 · doi:10.48550/arxiv.1809.09753

General volumes in the Orlicz-Brunn-Minkowski theory and a related Minkowski Problem II

2018· preprint· en· W4290980896 on OpenAlexfundno aff
Richard J. Gardner, Daniel Hug, Sudan Xing, Deping Ye

Bibliographic record

VenuearXiv (Cornell University) · 2018
Typepreprint
Languageen
FieldMathematics
TopicPoint processes and geometric inequalities
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaDeutsche ForschungsgemeinschaftNational Science Foundation
KeywordsConvex bodyMixed volumeMathematicsMinkowski spaceRegular polygonMeasure (data warehouse)CombinatoricsCurvatureMinkowski additionPolytopePure mathematicsMathematical analysisGeometryConvex hull

Abstract

fetched live from OpenAlex

The general dual volume $\dveV(K)$ and the general dual Orlicz curvature measure $\deV(K, \cdot)$ were recently introduced for functions $G: (0, \infty)\times \sphere\rightarrow (0, \infty)$ and convex bodies $K$ in $\R^n$ containing the origin in their interiors. We extend $\dveV(K)$ and $\deV(K, \cdot)$ to more general functions $G: [0, \infty)\times \sphere\rightarrow [0, \infty)$ and to compact convex sets $K$ containing the origin (but not necessarily in their interiors). Some basic properties of the general dual volume and of the dual Orlicz curvature measure, such as the continuous dependence on the underlying set, are provided. These are required to study a Minkowski-type problem for the dual Orlicz curvature measure. We mainly focus on the case when $G$ and $ψ$ are both increasing, thus complementing our previous work. The Minkowski problem asks to characterize Borel measures $μ$ on $\sphere$ for which there is a convex body $K$ in $\R^n$ containing the origin such that $μ$ equals $\deV(K, \cdot)$, up to a constant. A major step in the analysis concerns discrete measures $μ$, for which we prove the existence of convex polytopes containing the origin in their interiors solving the Minkowski problem. For general (not necessarily discrete) measures $μ$, we use an approximation argument. This approach is also applied to the case where $G$ is decreasing and $ψ$ is increasing, and hence augments our previous work. When the measures $μ$ are even, solutions that are origin-symmetric convex bodies are also provided under some mild conditions on $G$ and $ψ$. Our results generalize several previous works and provide more precise information about the solutions of the Minkowski problem when $μ$ is discrete or even.

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)0.002
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 score0.005
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.075
GPT teacher head0.223
Teacher spread0.148 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

Same venuearXiv (Cornell University)Same topicPoint processes and geometric inequalitiesFrench-language works237,207