SOFAR
swMATH ID: | 31665 |
Software Authors: | Uematsu, Yoshimasa; Fan, Yingying; Chen, Kun; Lv, Jinchi; Lin, Wei |
Description: | SOFAR: large-scale association network learning. Many modern big data applications feature large scale in both numbers of responses and predictors. Better statistical efficiency and scientific insights can be enabled by understanding the large-scale response-predictor association network structures via layers of sparse latent factors ranked by importance. Yet sparsity and orthogonality have been two largely incompatible goals. To accommodate both features, in this paper, we suggest the method of sparse orthogonal factor regression (SOFAR) via the sparse singular value decomposition with orthogonality constrained optimization to learn the underlying association networks, with broad applications to both unsupervised and supervised learning tasks, such as biclustering with sparse singular value decomposition, sparse principal component analysis, sparse factor analysis, and spare vector autoregression analysis. Exploiting the framework of convexity-assisted nonconvex optimization, we derive nonasymptotic error bounds for the suggested procedure characterizing the theoretical advantages. The statistical guarantees are powered by an efficient SOFAR algorithm with convergence property. Both computational and theoretical advantages of our procedure are demonstrated with several simulations and real data examples. |
Homepage: | https://arxiv.org/abs/1704.08349 |
Related Software: | camel; msda; spls; gglasso; JIVE; Cross; secure; rrpack; PEER; glmnet; R; ADMiRA; Jellyfish; SDPLR; LogConcDEAD; glasso |
Cited in: | 11 Documents |
Standard Articles
1 Publication describing the Software, including 1 Publication in zbMATH | Year |
---|---|
SOFAR: large-scale association network learning. Zbl 1432.68402 Uematsu, Yoshimasa; Fan, Yingying; Chen, Kun; Lv, Jinchi; Lin, Wei |
2019
|
all
top 5
Cited by 30 Authors
all
top 5
Cited in 7 Serials
Cited in 3 Fields
10 | Statistics (62-XX) |
2 | Computer science (68-XX) |
2 | Operations research, mathematical programming (90-XX) |