Large-Scale Independent Vector Analysis (IVA-G) via Coresets
Gabrielson B, Yang H, Vu T, Calhoun V, Adali T. Large-Scale Independent Vector Analysis (IVA-G) via Coresets. IEEE Transactions On Signal Processing 2024, 73: 230-244. DOI: 10.1109/tsp.2024.3517323.Peer-Reviewed Original ResearchJoint blind source separationIndependent vector analysisBlind source separationSubset selection methodJoint diagonalizationMultivariate Gaussian modelSource separationSignificant scalabilityComputational costCoresetMultiple datasetsSelection methodDatasetMeasure of discrepancyGaussian modelVector analysisNumerous extensionsScalabilityMethodMode Coresets for Efficient, Interpretable Tensor Decompositions: An Application to Feature Selection in fMRI Analysis
Gabrielson B, Yang H, Vu T, Calhoun V, Adali T. Mode Coresets for Efficient, Interpretable Tensor Decompositions: An Application to Feature Selection in fMRI Analysis. IEEE Access 2024, 12: 192356-192376. DOI: 10.1109/access.2024.3517338.Peer-Reviewed Original ResearchTensor decompositionSize of modern datasetsRank-1 tensorsComputational complexity scalesCore tensorTucker decompositionFeature selectionComputational complexitySelection schemeData tensorMultidimensional arraysRank-1CoresetTensor dataMatrix decompositionModern datasetsMassive sizeMyriad of applicationsMethod efficiencyDatasetSelection abilityComplexity scalesMeasure of discrepancyWell-approximatedDecomposition method
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