Sparse PCA from Sparse Linear Regression
To appear in NeurIPS ...
Bresler, Guy +2 more
openaire +2 more sources
Sparse matrices for weighted sparse recovery
We derived the first sparse recovery guarantees for weighted $\ell_1$ minimization with sparse random matrices and the class of weighted sparse signals, using a weighted versions of the null space property to derive these guarantees. These sparse matrices from expender graphs can be applied very fast and have other better computational complexities ...
openaire +2 more sources
MCMC Methods for Multi-Response Generalized Linear Mixed Models: The MCMCglmm R Package
Generalized linear mixed models provide a flexible framework for modeling a range of data, although with non-Gaussian response variables the likelihood cannot be obtained in closed form.
Jarrod Had
doaj
Sparse autoregressive neural networks for classical spin systems
Efficient sampling and approximation of Boltzmann distributions involving large sets of binary variables, or spins, are pivotal in diverse scientific fields even beyond physics.
Indaco Biazzo, Dian Wu, Giuseppe Carleo
doaj +1 more source
Sparse dimensionality reduction for analyzing single-cell-resolved interactions. [PDF]
Brunn N +4 more
europepmc +1 more source
Sparse-selective quantization for real-time cyber threat detection in large-scale networks. [PDF]
Xie Y, Wang R, Dong L.
europepmc +1 more source
Sparse testcrossing for early-stage genomic prediction of general combining ability to increase genetic gain in maize hybrid breeding programs. [PDF]
González-Diéguez DO +5 more
europepmc +1 more source
Structural Prior-Guided Weighted Low-Rank Denoising for Short-Wave Infrared Star Images. [PDF]
Wu C +5 more
europepmc +1 more source
RGB-conditioned frequency domain refinement for sparse-to-dense depth completion. [PDF]
Wang H, Tang Z, Pawara P, Chamchong R.
europepmc +1 more source
Filling of incomplete sinograms from sparse PET detector configurations using a residual U-Net. [PDF]
Leffler K +4 more
europepmc +1 more source

