The horseshoe prior has proven to be a noteworthy alternative for sparse Bayesian
estimation, but has previously suffered from two problems. First, there has been no …

Massive machine-type communication (mMTC) is a newly introduced service category in 5G
wireless communication systems to support a variety of Internet-of-Things (IoT) applications …

The horseshoe prior has proven to be a noteworthy alternative for sparse Bayesian
estimation, but as shown in this paper, the results can be sensitive to the prior choice for the …

This paper presents the use of spike-and-slab (SS) priors for discovering governing
differential equations of motion of nonlinear structural dynamic systems. The problem of …

The optimization of expensive to evaluate, black-box, mixed-variable functions, ie functions
that have continuous and discrete inputs, is a difficult and yet pervasive problem in science …

Compressive sensing (CS) applied to through-the-wall radar imaging (TWRI) exploits the
group sparsity of a target scene in the presence of wall clutter and multipath from enclosed …

This paper considers an uplink massive machine-type communication (mMTC) scenario,
where a large number of user devices are connected to a base station (BS). A novel grant …

Abstract Hamiltonian Monte Carlo (HMC) is one of the most successful sampling methods in
machine learning. However, its performance is significantly affected by the choice of …

With high-dimensional data emerging in various domains, sparse logistic regression models
have gained much interest of researchers. Variable selection plays a key role in both …

We address the problem of high-resolution radar imaging in low signal-to-noise ratio (SNR)
environments in an approximate Bayesian inference framework. First, the probabilistic …