Multiple Response Regression for Gaussian Mixture Models with Known Labels

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Joint Estimation of Multiple Precision Matrices with Common Structures.Double Sparsity Kernel Learning with Automatic Variable Selection and Data Extraction

P2860

Q40320755-68BFE440-E87C-46CC-86B5-D135392E4B0D Q57193347-C544EADB-E9EF-45F5-AC0B-0DADB9D2152D

P2860

Multiple Response Regression for Gaussian Mixture Models with Known Labels

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http://www.wikidata.org/entity/Q41859897

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2012 nî lūn-bûn

@nan

2012年の論文

@ja

2012年論文

@yue

2012年論文

@zh-hant

2012年論文

@zh-hk

2012年論文

@zh-mo

2012年論文

@zh-tw

2012年论文

@wuu

2012年论文

@zh

2012年论文

@zh-cn

name

Multiple Response Regression for Gaussian Mixture Models with Known Labels

@en

type

Item

label

Multiple Response Regression for Gaussian Mixture Models with Known Labels

@en

prefLabel

Multiple Response Regression for Gaussian Mixture Models with Known Labels

@en

P1476

Multiple Response Regression for Gaussian Mixture Models with Known Labels

@en

P2093

Wei Sun

http://www.w3.org/2001/XMLSchema#string

Wonyul Lee

http://www.w3.org/2001/XMLSchema#string

Ying Du

http://www.w3.org/2001/XMLSchema#string

Yufeng Liu

http://www.w3.org/2001/XMLSchema#string

P2860

Integrated genomic analysis identifies clinically relevant subtypes of glioblastoma characterized by abnormalities in PDGFRA, IDH1, EGFR, and NF1

Comprehensive genomic characterization defines human glioblastoma genes and core pathways

Semi-supervised methods to predict patient survival from gene expression data

A general framework for weighted gene co-expression network analysis

Hierarchical organization of modularity in metabolic networks

Sparse Multivariate Regression With Covariance Estimation.

Sparse inverse covariance estimation with the graphical lasso.

ARAP2 effects on the actin cytoskeleton are dependent on Arf6-specific GTPase-activating-protein activity and binding to RhoA-GTP.

GLI2 transcription factor mediates cytokine cross-talk in the tumor microenvironment.

Joint estimation of multiple graphical models

P31

scholarly article

P356

10.1002/SAM.11158

http://www.w3.org/2001/XMLSchema#string

P433

http://www.w3.org/2001/XMLSchema#string

P478

http://www.w3.org/2001/XMLSchema#string

P50

D. Neil Hayes

P577

2012-12-01T00:00:00Z

http://www.w3.org/2001/XMLSchema#dateTime

P698

24416092

http://www.w3.org/2001/XMLSchema#string

P932

3885347

http://www.w3.org/2001/XMLSchema#string

Multiple Response Regression for Gaussian Mixture Models with Known Labels

about

P2860

P2860

Multiple Response Regression for Gaussian Mixture Models with Known Labels

description

name

type

label

prefLabel

P1433

P1476

P2093

P2860

P31

P356

P433

P478

P50

P577

P698

P932

P356

P1433

P1476

P2093

P2860

P31

P356

P433

P478

P50

P577

P698

P932