2024
Schrödinger-Föllmer Sampler
Huang J, Jiao Y, Kang L, Liao X, Liu J, Liu Y. Schrödinger-Föllmer Sampler. IEEE Transactions On Information Theory 2024, 71: 1283-1299. DOI: 10.1109/tit.2024.3522494.Peer-Reviewed Original ResearchNon-asymptotic error boundsEuler–Maruyama discretizationMarkov chain Monte Carlo methodsEuler–MaruyamaUnit intervalError boundsWasserstein distancePosterior distributionSampling distributionNumerical experimentsUnnormalized distributionsTarget distributionMonte Carlo methodMachine learningProbability distributionBayesian inferenceDegenerate formErgodicityDiffusion processCarlo methodTheoretical analysisInferenceBoundsSFSWassersteinNonasymptotic Bounds for Adversarial Excess Risk under Misspecified Models
Liu C, Jiao Y, Wang J, Huang J. Nonasymptotic Bounds for Adversarial Excess Risk under Misspecified Models. SIAM Journal On Mathematics Of Data Science 2024, 6: 847-868. DOI: 10.1137/23m1598210.Peer-Reviewed Original ResearchNetwork analysis of smoking-related sleep characteristics in Chinese adults
Xie Y, Sun P, Huang H, Wu J, Ba Y, Zhou G, Yu F, Zhang D, Zhang Y, Qie R, Hu Z, Zou K, Zhang Y. Network analysis of smoking-related sleep characteristics in Chinese adults. Annals Of Medicine 2024, 56: 2332424. PMID: 38527416, PMCID: PMC10964831, DOI: 10.1080/07853890.2024.2332424.Peer-Reviewed Original ResearchConceptsLate bedtimeMultiple sleep characteristicsChinese adultsCancer-related risk factorsPotential core domainsSleep characteristicsSleep health promotionLogistic regression modelsShort sleep durationHealth promotionTobacco preventionCurrent smokingSmoking cessationSmoking intensitySmoking behaviorHeavy smokingSleep durationNap timeSmokingPositive associationRisk factorsRegression modelsYoung adultsAdultsAssociationApplication of Survival Quilts for prognosis prediction of gastrectomy patients based on the Surveillance, Epidemiology, and End Results database and China National Cancer Center Gastric Cancer database
Zhao L, Niu P, Wang W, Han X, Luan X, Huang H, Zhang Y, Zhao D, Gao J, Chen Y. Application of Survival Quilts for prognosis prediction of gastrectomy patients based on the Surveillance, Epidemiology, and End Results database and China National Cancer Center Gastric Cancer database. Journal Of The National Cancer Center 2024, 4: 142-152. PMID: 39282580, PMCID: PMC11390701, DOI: 10.1016/j.jncc.2024.01.007.Peer-Reviewed Original ResearchCancer-specific survivalSEER validation setCancer-specific survival modelGastric cancer patientsOverall survivalArea under the curveGastrectomy patientsHigh-risk groupCancer patientsChina National Cancer Center Gastric Cancer DatabaseNational Cancer Center Gastric Cancer DatabasePrognosis predictionTumor-node-metastasis (TNM) stageEnd Results databaseGastric cancer databaseValidation setPrognostic value of risk scoreTest 6 monthsPredicting 6-monthAccurate prognosis predictionInternal validation setNeoadjuvant therapyResults databaseCancer DatabasePrognostic valueDeep Dimension Reduction for Supervised Representation Learning
Huang J, Jiao Y, Liao X, Liu J, Yu Z. Deep Dimension Reduction for Supervised Representation Learning. IEEE Transactions On Information Theory 2024, 70: 3583-3598. DOI: 10.1109/tit.2023.3340658.Peer-Reviewed Original ResearchRepresentation learningStandard deep learning modelsHigh-dimensional complex dataSupervised representation learningRepresentation learning tasksDeep neural networksEffective data representationsContext of classificationDeep learning modelsNonparametric representationDimension reduction methodDimension reduction approachLearned representationsPromote disentanglementData representationNeural networkComplex dataLearning modelsDimension reductionTarget representationLearning tasksReduction methodSufficient dimension reduction methodsLow-dimensionalConditional independence
2023
Online inference in high-dimensional generalized linear models with streaming data.
Luo L, Han R, Lin Y, Huang J. Online inference in high-dimensional generalized linear models with streaming data. Electronic Journal Of Statistics 2023, 17: 3443-3471. PMID: 39188774, PMCID: PMC11346802, DOI: 10.1214/23-ejs2182.Peer-Reviewed Original ResearchOnline inference with debiased stochastic gradient descent
Han R, Luo L, Lin Y, Huang J. Online inference with debiased stochastic gradient descent. Biometrika 2023, 111: 93-108. DOI: 10.1093/biomet/asad046.Peer-Reviewed Original ResearchStochastic gradient descent algorithmHigh-dimensional statisticsOne-pass algorithmGradient descent algorithmHigh-dimensional dataAsymptotic normalityText datasetsSparsity levelOnline fashionOnline inferenceData distributionTime complexitySpace complexityDescent algorithmStatistical inferenceUpdate stepNumerical experimentsAlgorithmDebiasing techniquesMild conditionsInferenceSparsityEstimationConfidence intervalsDatasetPhysical activity domains and patterns with risk of depressive symptoms: A cross-sectional study in China
Qie R, Huang H, Sun P, Wu J, Ba Y, Zhou G, Yu F, Zhang D, Zhang Y, Xie Y, Hu Z, Zou K, Zhang Y. Physical activity domains and patterns with risk of depressive symptoms: A cross-sectional study in China. Journal Of Affective Disorders 2023, 337: 120-127. PMID: 37263360, DOI: 10.1016/j.jad.2023.05.091.Peer-Reviewed Original ResearchConceptsLeisure-time PARisk of depressive symptomsTransportation PAPA patternsHousehold PADepressive symptomsCross-sectional studyOccupational PAOdds ratioPhysical activityDomain-specific physical activityPhysical activity domainsConfidence intervalsCalculate odds ratiosCross-sectional designNon-linear associationPA domainsLogistic regression analysisInverse associationInactive groupInconsistent associationsLatent class analysisPositive associationHealth benefitsLow riskDeep nonparametric regression on approximate manifolds: Nonasymptotic error bounds with polynomial prefactors
Jiao Y, Shen G, Lin Y, Huang J. Deep nonparametric regression on approximate manifolds: Nonasymptotic error bounds with polynomial prefactors. The Annals Of Statistics 2023, 51 DOI: 10.1214/23-aos2266.Peer-Reviewed Original ResearchPhysical activity and risk of lung cancer: A systematic review and dose-response meta-analysis of cohort studies
Qie R, Han M, Huang H, Sun P, Xie Y, He J, Zhang Y. Physical activity and risk of lung cancer: A systematic review and dose-response meta-analysis of cohort studies. Journal Of The National Cancer Center 2023, 3: 48-55. PMID: 39036308, PMCID: PMC11256557, DOI: 10.1016/j.jncc.2022.12.003.Peer-Reviewed Original ResearchLeisure-time physical activityOccupational physical activityLung cancer riskCancer riskPhysical activityMetabolic equivalent of task hoursLeisure-time physical activity levelsDose-response meta-analysis of cohort studiesIncident cases of lung cancerMeta-analysis of cohort studiesRisk of lung cancerConfidence intervalsDose-response meta-analysisApproximately U-shaped associationU-shaped associationLung cancerMetabolic equivalentsCases of lung cancerWeb of ScienceDose-response analysisIncident casesFixed-effects modelStanding occupationCancer associationStudy participantsHETEROGENEITY ANALYSIS VIA INTEGRATING MULTI-SOURCES HIGH-DIMENSIONAL DATA WITH APPLICATIONS TO CANCER STUDIES.
Zhong T, Zhang Q, Huang J, Wu M, Ma S. HETEROGENEITY ANALYSIS VIA INTEGRATING MULTI-SOURCES HIGH-DIMENSIONAL DATA WITH APPLICATIONS TO CANCER STUDIES. Statistica Sinica 2023, 33: 729-758. PMID: 38037567, PMCID: PMC10686523, DOI: 10.5705/ss.202021.0002.Peer-Reviewed Original Research
2022
Etiology of lung cancer: Evidence from epidemiologic studies
Zou K, Sun P, Huang H, Zhuo H, Qie R, Xie Y, Luo J, Li N, Li J, He J, Aschebrook-Kilfoy B, Zhang Y. Etiology of lung cancer: Evidence from epidemiologic studies. Journal Of The National Cancer Center 2022, 2: 216-225. PMID: 39036545, PMCID: PMC11256564, DOI: 10.1016/j.jncc.2022.09.004.Peer-Reviewed Original ResearchLung cancerRisk factorsEpidemiologic studiesSpecific lung cancer subtypesCommon histologic subtypeIncidence of adenocarcinomaSquamous cell carcinomaAdditional risk factorsLung cancer casesLung cancer subtypesHistologic subtypeCell carcinomaCancer incidenceCancer casesOccupational exposureCurrent evidenceGene-environment interactionsCancer subtypesReal-world settingDiesel fumesExposure individualsCancerSubtypesIncidenceFuture studiesResponse best-subset selector for multivariate regression with high-dimensional response variables
Hu J, Huang J, Liu X, Liu X. Response best-subset selector for multivariate regression with high-dimensional response variables. Biometrika 2022, 110: 205-223. DOI: 10.1093/biomet/asac037.Peer-Reviewed Original ResearchClinicopathological characteristics, survival outcomes, and genetic alterations of younger patients with gastric cancer: Results from the China National Cancer Center and cBioPortal datasets
Niu P, Huang H, Zhao L, Wang T, Zhang X, Wang W, Zhang Y, Guo C, Zhao D, Chen Y. Clinicopathological characteristics, survival outcomes, and genetic alterations of younger patients with gastric cancer: Results from the China National Cancer Center and cBioPortal datasets. Cancer Medicine 2022, 11: 3057-3073. PMID: 35486034, PMCID: PMC9385592, DOI: 10.1002/cam4.4669.Peer-Reviewed Original ResearchConceptsNational Cancer Center Gastric Cancer DatabasePTNM stage IIIYounger patientsSurvival outcomesOlder patientsGastric cancerOverall survivalClinicopathological characteristicsChina National Cancer Center Gastric Cancer DatabaseGenetic alterationsImproving survival of young patientsSurvival outcomes of young patientsStage IIIOutcomes of young patientsSurvival of young patientsPoorly differentiated lesionsPTNM stage IVYoung GC patientsCTNNB1 gene mutationsGastric cancer databaseCox proportional hazards modelsKaplan-Meier estimatesProportional hazards modelMSKCC databasesCancer DatabaseInternational patterns and trends of childhood and adolescent cancer, 1978-2012
Zhao Y, Sun P, Xiao J, Jin L, Ma N, Li Z, Feng G, Huang H, Deziel N, Ma X, Ni X, Zhang Y. International patterns and trends of childhood and adolescent cancer, 1978-2012. Journal Of The National Cancer Center 2022, 2: 78-89. PMID: 39034956, PMCID: PMC11256536, DOI: 10.1016/j.jncc.2022.02.001.Peer-Reviewed Original ResearchCancer incidence ratesIncidence rateCancer incidenceMalignant central nervous system tumorsCentral nervous system tumorsOverall childhood cancerIncidence of lymphomaNervous system tumorsLeukemia incidence ratesSystem tumorsTesticular cancerChildhood cancerThyroid cancerAdolescent cancerKidney cancerJoinpoint regressionCancer incidentsAge groupsCancerCancer typesIncidenceTemporal trendsMethods DataAdolescentsChildren
2021
Regularized projection score estimation of treatment effects in high-dimensional quantile regression
Cheng C, Feng X, Huang J, Liu X. Regularized projection score estimation of treatment effects in high-dimensional quantile regression. Statistica Sinica 2021 DOI: 10.5705/ss.202019.0247.Peer-Reviewed Original Research
2017
A group adaptive elastic-net approach for variable selection in high-dimensional linear regression
Hu J, Huang J, Qiu F. A group adaptive elastic-net approach for variable selection in high-dimensional linear regression. Science China Mathematics 2017, 61: 173-188. DOI: 10.1007/s11425-016-0071-x.Peer-Reviewed Original ResearchAdaptive elastic-netHigh-dimensional linear regressionProblem of group selectionElastic-netOracle propertyOracle inequalitiesHigh-dimensional problemsVariable selectionGroup structureSample sizeModel selectionCollinearity problemElastic netOracleElastic-net approachHigh-dimensionalCompetitive methodsData studiesLinear regression modelsProblemInequalityModel consistencyGroup numberStatistical modelInference
2015
Asymptotic properties of Lasso in high-dimensional partially linear models
Ma C, Huang J. Asymptotic properties of Lasso in high-dimensional partially linear models. Science China Mathematics 2015, 59: 769-788. DOI: 10.1007/s11425-015-5093-2.Peer-Reviewed Original ResearchHigh-dimensional partially linear modelsPartially linear modelsLinear partPerformance of variable selectionFinite sample performanceNonparametric function estimationRate of convergenceTruncated series expansionNonparametric componentAsymptotic propertiesNonparametric functionOracle inequalitiesRegularity conditionsSufficient conditionsLasso estimatorPolynomial splinesFunction estimationSparsity assumptionLinear modelVariable selectionSimulation studySeries expansionEstimation errorRegression coefficientsLinear component
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