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Collective Support Recovery for Multi-Design ...
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2014年11月26日 — Abstract: The multi-design multi-response linear regression problem is investigated, in which design matrices are Gaussian with covariance ...
Collective Support Recovery for Multi-Design ...
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由 W Wang 著作2014被引用 13 次 — One application of the MDMR linear regression model is to jointly learning multiple Gaussian Markov network structures. In this context, it solves a multi-task ...
Collective Support Recovery for Multi-Design Multi-Response ...
CMU School of Computer Science
http://www.cs.cmu.edu › Wang_Liang_Xing_IT14
CMU School of Computer Science
http://www.cs.cmu.edu › Wang_Liang_Xing_IT14
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由 W Wang 著作被引用 13 次 — One application of the MDMR linear regression model is to jointly learning multiple Gaussian Markov network structures. In this context, it solves a multi-task ...
Collective Support Recovery for Multi-Design Multi-Response ...
Experts@Syracuse
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Experts@Syracuse
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The multi-design multi-response linear regression problem is investigated, in which design matrices are Gaussian with covariance matrices Σ(1:K) = Σ(1), ...
Weiguang Wang, Yingbin Liang, Eric P. Xing
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Collective Support Recovery for Multi-Design Multi-Response Linear Regression. Weiguang Wang, Yingbin Liang, Eric P. Xing. 2015 IEEE Transactions on ...
Support union recovery in high-dimensional multivariate ...
Project Euclid
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由 G Obozinski 著作2011被引用 395 次 — In multivariate regression, a K-dimensional response vector is regressed upon a common set of p covariates, with a matrix B∗ ∈ Rp×K of regression.
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Bayesian Method for Support Union Recovery in Multivariate ...
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Example 3.4 Consider another multi-response linear regression model. There are M = 10 regression models and p = 400 predicator variables of length n = 100.
[PDF] Union Support Recovery in Multi-task Learning
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Collective Support Recovery for Multi-Design Multi-Response Linear Regression · Weiguang WangYingbin LiangE. Xing. Computer Science, Mathematics. IEEE ...
Sharp Threshold for Multivariate Multi-Response Linear ...
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The goal is to recover the support union of all regression vectors using l 1 / l 2 l_1/l_2 -regularized Lasso. We characterize sufficient and necessary ...
Parallel integrative learning for large-scale multi-response ...
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由 R Dong 著作2021被引用 4 次 — In this paper, we propose a scalable and computationally efficient procedure, called PEER, for large-scale multi-response regression with incomplete outcomes.