The Relevance Vector Machine (RVM) introduced by Tipping is a probabilistic model similar to the widespread Support Vector Machines (SVM), but where the training takes place in a Bayesian framework, and where predictive distributions of the outputs instead of point estimates are obtained. In this paper we focus on the use of RVM’s for regression. We modify this method for training generalized l...

We present an approximate Bayesian method for regression and classification with models linear in the parameters. Similar to the Relevance Vector Machine (RVM), each parameter is associated with an expansion vector. Unlike the RVM, the number of expansion vectors is specified beforehand. We assume an overall Gaussian prior on the parameters and find, with a gradient based process, the expansion...

We introduce a new Bayesian approach to the variable selection problem which we term Bayesian Shrinkage Variable Selection (BSVS ). This approach is inspired by the Relevance Vector Machine (RVM ), which uses a Bayesian hierarchical linear setup to do variable selection and model estimation. RVM is typically applied in the context of kernel regression although it is also suitable in the standar...

The original RVM classification model uses the logistic link function to build likelihood making hard be conducted since posterior of weight parameter has no closed-form solution. This article proposes probit approach instead one for in model, namely PRVM (RVM with function). We show that follows Multivariate Normal distribution and achieves a A latent variable is needed our algorithms simplify...

Many clinical case reports have suggested that sustained opioid exposure can elicit unexpected, paradoxical pain. Here, we explore the possibility that (1) opioid-induced pain results from tonic activation of descending pain facilitation arising in the rostral ventromedial medulla (RVM) and (2) the presence of such pain manifests behaviorally as antinociceptive tolerance. Rats implanted subcuta...

Each of the lateral capsular division of central nucleus of amygdala(CeLC), periaqueductal gray (PAG), rostral ventromedial medulla(RVM) and spinal cord has been proved to contribute to the development of opioid-induced hyperalgesia(OIH). Especially, Ca2+/calmodulin-dependent protein kinase IIα (CaMKIIα) in CeLC and spinal cord seems to play a key role in OIH modulation. However, the pain pathw...

This study examined a mechanism responsible for the enhanced antihyperalgesic and antinociceptive effects of the mu opioid receptor agonist (ORA) [D-Ala(2), NMePhe(4), Gly(5)-ol]enkephalin (DAMGO) microinjected in the rostroventromedial medulla (RVM) of rats with inflammatory injury induced by injection of complete Freund's adjuvant (CFA) in one hindpaw. In rats injected with CFA 4 hr earlier, ...

Peripheral nerve injuries (PNIs) may result in cellular and molecular changes in supraspinal structures possibly involved in neuropathic pain (NPP) maintenance. Activated glial cells in specific supraspinal subregions may affect the facilitatory role of descending pathways. Sterile chronic compression injury (sCCI) and complete sciatic nerve transection (CSNT) in rats were used as NPP models to...

The modulatory effects of electrical and chemical (glutamate) stimulation in the rostral ventromedial medulla (RVM) on spinal nociceptive transmission and a spinal nociceptive reflex were studied in rats. Electrical stimulation at a total 86 sites in the RVM in the medial raphe nuclei (n = 54) and adjacent gigantocellular areas (n = 32) produced biphasic (facilitatory and inhibitory, n = 43) or...

Long-term streamflow forecasting is crucial to reservoir scheduling and water resources management. However, due to the complexity of internally physical mechanisms in streamflow process and the influence of many random factors, long-term streamflow forecasting is a difficult issue. In the article, we mainly investigated the ability of the Relevance Vector Machine (RVM) model and its applicabil...