The thalamic reticular nucleus (nRT) is composed entirely of GABAergic inhibitory neurones that receive input from pyramidal cortical neurones and excitatory relay cells of the ventrobasal complex of the thalamus (VB). It plays a major role in the synchrony of thalamic networks, yet the synaptic connections it receives from VB cells have never been fully physiologically characterised. Here, who...

Variational Bayes (VB), variational maximum likelihood (VML), restricted maximum likelihood (ReML), and maximum likelihood (ML) are cornerstone parametric statistical estimation techniques in the analysis of functional neuroimaging data. However, the theoretical underpinnings of these model parameter estimation techniques are rarely covered in introductory statistical texts. Because of the wide...

The EM training algorithm of the classical i-vector extractor [1, 2] is often incorrectly described as a maximum-likelihood method. The i-vector model is however intractable—the likelihood itself and the hidden-variable posteriors needed for the EM algorithm cannot be computed in closed form. We show here that the classical i-vector extractor recipe is actually a mean-field variational Bayes (V...

In this paper we propose a connection balanced routing in mobile ad-hoc networks (MANETs) using backbone update messages. Virtual-Backbone (VB) construction is very familiar, to overcome broadcast storm problem in wireless networks. In real time, during the movement of nodes in MANET, more number of nodes added in a particular node (say a VB node), it leads poor quality of service in multi-hop ...

This work presents the first experimental demonstration of the virtual bandwidth synthetic aperture radar (VB-SAR) imaging scheme. VB-SAR is a newly-developed subsurface imaging technique which, in stark contrast to traditional close-proximity ground penetrating radar (GPR) schemes, promises imaging from remote standoff platforms such as aircraft and satellites. It specifically exploits the dif...

In this paper, we propose a unified approach to VB (variational Bayes) [1] in symbolicstatistical modeling via propositionalization1. By propositionalization we mean, broadly, expressing and computing probabilistic models such as BNs (Bayesian networks) [2] and PCFGs (probabilistic context free grammars) [3] in terms of propositional logic that considers propositional variables as binary random...

Variational methods for approximate inference in machine learning often adapt a parametric probability distribution to optimize a given objective function. This view is especially useful when applying variational Bayes (VB) to models outside the conjugate-exponential family. For them, variational Bayesian expectation maximization (VB EM) algorithms are not easily available, and gradient-based m...

In the Red-Blue Dominating Set problem, we are given a bipartite graph G = (VB ∪ VR, E) and an integer k, and asked whether G has a subset D ⊆ VB of at most k ‘blue’ vertices such that each ‘red’ vertex from VR is adjacent to a vertex in D. We provide the first explicit linear kernel for this problem on planar graphs.

BACKGROUND More than 100,000 patients each year in Denmark experience nosocomial infections, erroneous medication, or pressure ulcers while hospitalized. The Danish Safer Hospital Program includes 12 bundles for improving patient safety through the introduction and maintenance of evidence-based routine treatment or standard procedures. OBJECTIVE To determine cost-effectiveness of implementing...