This paper introduces an R package that implements Simultaneous non-Gaus...
Deep learning models achieve state-of-the art results in predicting bloo...
Sequencing-based technologies provide an abundance of high-dimensional
b...
Canonical correlation analysis (CCA) is a standard tool for studying
ass...
The prevalence of data collected on the same set of samples from multipl...
Continuous glucose monitors (CGMs) are increasingly used to measure bloo...
We present `latentcor`, an R package for correlation estimation from dat...
Microorganisms play a critical role in host health. The advancement of
h...
We consider the problem of extracting joint and individual signals from
...
Latent Gaussian copula models provide a powerful means to perform multi-...
Large-sample data became prevalent as data acquisition became cheaper an...
As advances in technology allow the acquisition of complementary informa...
We consider the two-group classification problem and propose a kernel
cl...
Multi-view data, that is matched sets of measurements on the same subjec...
Sparse linear discriminant analysis via penalized optimal scoring is a
s...
Canonical correlation analysis investigates linear relationships between...
The TREX is a recently introduced approach to sparse linear regression. ...
We consider the problem of high-dimensional classification between the t...
The increased availability of the multi-view data (data on the same samp...
The abundance of high-dimensional data in the modern sciences has genera...
The TREX is a recently introduced method for performing sparse
high-dime...
This article considers the problem of multi-group classification in the
...
We investigate the difference between using an ℓ_1 penalty versus an
ℓ_1...
This article considers the problem of sparse estimation of canonical vec...
It is well known that in a supervised classification setting when the nu...