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Cafe: Improved Federated Data Imputation by Leveraging Missing Data Heterogeneity

IEEE Transactions on Knowledge and Data Engineering(2025)10.1109/tkde.2025.3537403Source: DataRank Database

Cafe: Improved Federated Data Imputation by Leveraging Missing Data Heterogeneity is a research paper published in IEEE Transactions on Knowledge and Data Engineering (2025). On theSindex it has a DataRank of 0. It has been cited 10 times.

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0DataRank · unranked

Scored on demand from live citation data

Open Access10 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (2 grants)Impact (FWCI 13.04)OA: greenTopics (15)IDs (PubMed, PMC, OpenAlex)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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Authors (4)

Hafiz Asif ORCID,Xinyue Wang ORCID,Jaideep Vaidya ORCID,Sitao Min ORCID

Live enrichment

PubMed:40322292 PMC:PMC12048026 OpenAlex:https://openalex.org/W4406983014

NIH

Grant: R35GM134927

NIH

Grant: R01LM014520

FWCI

13.04

Citation Percentile

1.0%

Citation Trend

2025

2026

greenLicense: https://doi.org/10.15223/policy-029

repositoryhttps://pmc.ncbi.nlm.nih.gov/articles/PMC12048026/

publisherhttp://xplorestaging.ieee.org/ielx8/69/10948402/10858753.pdf?arnumber=10858753

journalhttps://doi.org/10.1109/tkde.2025.3537403

repositoryhttps://pubmed.ncbi.nlm.nih.gov/40322292

Fields of Study

Privacy-Preserving Technologies in DataData Quality and ManagementCryptography and Data Security

Keywords

Computer scienceImputation (statistics)Missing dataData miningData modelingInformation retrievalDatabaseMachine learningData QualityMissing Data ImputationData HeterogeneityFederated Learning