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Unknown

10.48550/arxiv.1811.04422Source: DataRank Database

Unknown is a research paper. On theSindex it has a DataRank of 0.502. It has been cited 9 times, with 5 citing works in its 1-hop citation network.

N/A

0.502DataRank · unranked

Scored on demand from live citation data

9 citations · 5 citing works in its network

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DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?

›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (3 grants)OA: greenTopics (27)IDs (PubMed, OpenAlex)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (0/2)

Interoperable (0/2)

Reusable (0/3)

FAIR checklist signals are shown for context only and do not affect DataRank scoring.

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DataRank Breakdown

Base Score 69%Citation Network 31%

Base Score Contribution

0.345

From this paper's citation signal

Citation Network Contribution

0.157

From 5 citing papers with measurable signal

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Top 5 citers driving the network score

Ranked by each citer's contribution to N(p) — log1p(C_q) divided by its reference count — out of 5 citers.

Finite-Time Convergence of Continuous-Time Optimization Algorithms via Differential Inclusions
arXiv (Cornell University)20196 citations30 referencesContributes 0.065
Learning-based attacks in Cyber-Physical Systems: Exploration, Detection, and Control Cost trade-offs
arXiv (Cornell University)20206 citations50 referencesContributes 0.039
Data Poisoning Attack on Deep Neural Network and Some Defense Methods
202011 citations67 referencesContributes 0.037
Secure-UCB: Saving Stochastic Bandits from Poisoning Attacks via Limited Data Verification.
arXiv (Cornell University)20213 citations49 referencesContributes 0.028
Teaching an Active Learner with Contrastive Examples
arXiv (Cornell University)20211 citations46 referencesContributes 0.015

Live enrichment

PubMed:30945415 OpenAlex:https://openalex.org/W2900159906

National Science Foundation

Grant: 1545481

NRT-DESE LUCID: A project-focused cross-disciplinary graduate training program for data-enabled research in human and machine learning and teaching

National Science Foundation

Grant: 1837132

FMitF: Collaborative Research: Formal Methods for Machine Learning System Design

National Science Foundation

Grant: 1704117

SHF: Medium: Formal Methods for Program Fairness

greenLicense: arXiv Non-Exclusive Distribution

repositoryhttps://arxiv.org/pdf/1811.04422

repositoryhttp://arxiv.org/abs/1811.04422

repositoryhttps://doi.org/10.48550/arxiv.1811.04422

https://dx.doi.org/10.48550/arxiv.1811.04422

Fields of Study

Adversarial Robustness in Machine LearningAnomaly Detection Techniques and ApplicationsAdvanced Bandit Algorithms ResearchMachine Learning (cs.LG)Machine Learning (stat.ML)FOS: Computer and information sciences0202 electrical engineering, electronic engineering, information engineering02 engineering and technology01 natural sciences0105 earth and related environmental sciences

Keywords

Adversarial systemAdversarial machine learningAdversaryComputer scienceArtificial intelligenceReinforcement learningControl (management)HarmMachine learningComputer securityPsychologySocial psychologyFOS: Computer and information sciencesComputer Science - Machine LearningStatistics - Machine LearningMachine Learning (stat.ML)Machine Learning (cs.LG)