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1102.4110
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Joint and individual variation explained (JIVE) for integrated analysis of multiple data types
Annals of Applied Statistics (AOAS), 2011
20 February 2011
E. Lock
K. Hoadley
J. S. Marron
A. Nobel
DRL
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Papers citing
"Joint and individual variation explained (JIVE) for integrated analysis of multiple data types"
50 / 63 papers shown
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D-CDLF: Decomposition of Common and Distinctive Latent Factors for Multi-view High-dimensional Data
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Joint Linked Component Analysis for Multiview Data
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17 Jun 2024
Learning Joint and Individual Structure in Network Data with Covariates
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Bayesian Joint Additive Factor Models for Multiview Learning
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Contrastive Learning on Multimodal Analysis of Electronic Health Records
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Robust Principal Component Analysis using Density Power Divergence
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Multimodal Understanding Through Correlation Maximization and Minimization
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Marc Niethammer
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Bayesian Simultaneous Factorization and Prediction Using Multi-Omic Data
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Multimodal Learning for Multi-Omics: A Survey
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Exponential canonical correlation analysis with orthogonal variation
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Yunfeng Zhang
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Modern Views of Machine Learning for Precision Psychiatry
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Joint Gaussian Graphical Model Estimation: A Survey
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Non-Euclidean Analysis of Joint Variations in Multi-Object Shapes
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Filtrated Common Functional Principal Components for Multivariate Functional data
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205
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Double-matched matrix decomposition for multi-view data
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Irina Gaynanova
184
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Orthogonalized Kernel Debiased Machine Learning for Multimodal Data Analysis
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Lexin Li
289
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12 Mar 2021
sJIVE: Supervised Joint and Individual Variation Explained
Computational Statistics & Data Analysis (CSDA), 2021
E. Palzer
C. Wendt
R. Bowler
C. Hersh
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E. Lock
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139
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26 Feb 2021
Blind signal decomposition of various word embeddings based on join and individual variance explained
Yikai Wang
Weijian Li
165
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30 Nov 2020
Finding Groups of Cross-Correlated Features in Bi-View Data
Journal of machine learning research (JMLR), 2020
Miheer Dewaskar
John Palowitch
Mark He
M. Love
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338
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mvlearn: Multiview Machine Learning in Python
Ronan Perry
Gavin Mischler
Richard Guo
T. Lee
Alexander Chang
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Iain Carmichael
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Alexandre Gramfort
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Semi-Supervised Multi-aspect Detection of Misinformation using Hierarchical Joint Decomposition
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Neil Shah
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Benjamin Risk
Irina Gaynanova
249
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Directionally Dependent Multi-View Clustering Using Copula Model
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K. Afrin
A. Iquebal
Mostafa Karimi
Allyson Souris
Se Yoon Lee
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205
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17 Mar 2020
Bidimensional linked matrix factorization for pan-omics pan-cancer analysis
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K. Hoadley
289
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CDPA: Common and Distinctive Pattern Analysis between High-dimensional Datasets
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Hai Shu
Zhe Qu
246
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Integrative Generalized Convex Clustering Optimization and Feature Selection for Mixed Multi-View Data
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Minjie Wang
Genevera I. Allen
300
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Regularized and Smooth Double Core Tensor Factorization for Heterogeneous Data
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George Michailidis
465
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24 Nov 2019
Integrative Factor Regression and Its Inference for Multimodal Data Analysis
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Quefeng Li
Lexin Li
323
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11 Nov 2019
Supervised tensor decomposition with features on multiple modes
Journal of Computational And Graphical Statistics (JCGS), 2019
Jiaxin Hu
Chanwoo Lee
Miaoyan Wang
264
12
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21 Oct 2019
Joint, Partially-joint, and Individual Independent Component Analysis in Multi-Subject fMRI Data
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Mansooreh Pakravan
M. Shamsollahi
132
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09 Sep 2019
Fusing heterogeneous data sets
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156
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Deep Multi-View Learning via Task-Optimal CCA
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Roland Kwitt
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Marc Niethammer
216
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Integrative Factorization of Bidimensionally Linked Matrices
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E. Lock
288
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Co-Separating Sounds of Visual Objects
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Kristen Grauman
477
223
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16 Apr 2019
Separating common (global and local) and distinct variation in multiple mixed types data sets
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J. Westerhuis
A. Smilde
235
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17 Feb 2019
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