2024
TENSOR QUANTILE REGRESSION WITH LOW-RANK TENSOR TRAIN ESTIMATION.
Liu Z, Lee C, Zhang H. TENSOR QUANTILE REGRESSION WITH LOW-RANK TENSOR TRAIN ESTIMATION. The Annals Of Applied Statistics 2024, 18: 1294-1318. PMID: 38682044, PMCID: PMC11046526, DOI: 10.1214/23-aoas1835.Peer-Reviewed Original ResearchTensor trainCoefficient tensorRate of convergenceLow-rankQuantile regression frameworkApproximation-based methodVariation penaltyHuman intelligenceQuantile regression modelEstimation algorithmMRI image dataAsymptotic normalityArray of imagesScalar outcomeEmpirical performanceImage dataTrained estimatorDimensionalityNumerical studyMagnetic resonance imaging imagesQuantile regressionTensorRegression frameworkTT estimationImagesGeometric scattering on measure spaces
Chew J, Hirn M, Krishnaswamy S, Needell D, Perlmutter M, Steach H, Viswanath S, Wu H. Geometric scattering on measure spaces. Applied And Computational Harmonic Analysis 2024, 70: 101635. PMID: 40686586, PMCID: PMC12272135, DOI: 10.1016/j.acha.2024.101635.Peer-Reviewed Original ResearchConvolutional neural networkGeometric deep learningDeep learningNeural networkSuccess of convolutional neural networksModel of convolutional neural networkMeasure spaceScattering transformData-driven graphsInvariance propertiesRiemannian manifoldsNon-Euclidean structureUndirected graphWavelet-based transformCompact Riemannian manifoldsData structuresRate of convergenceSpherical imagesNetwork stabilityHigh-dimensional single-cell dataData setsDirected graphDiffusion-mapsSigned graphGraph
2019
Sparse principal component analysis with missing observations
Park S, Zhao H. Sparse principal component analysis with missing observations. The Annals Of Applied Statistics 2019, 13: 1016-1042. DOI: 10.1214/18-aoas1220.Peer-Reviewed Original ResearchHigh-dimensional settingsPrincipal subspaceStep estimation procedureRate of convergenceSparse principal component analysisDimensional settingSimulated examplesMissing observationsStatistical methodsEstimation procedureSparse PCA methodsSingle-cell dataSubspacePCA methodSingle-cell RNA-sequencing dataNumber of featuresCompetitive performancePrincipal component analysisConvergenceSample sizeEstimationWide rangeComponent analysis
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