Search results for "BAYESIAN"

Manuale pratico per la diagnosi in reumatologia. Il ragionamento bayesiano applicato ai criteri diagnostici dell'American College of Reumatology. I e…

2009

Title : Exposure Assessment to Air Pollution of Children Living in the High Risk Area of Milazzo – Valle del Mela (Sicily): a Bayesian Kriging Approa…

2011

Bayesian joint modeling of bivariate longitudinal and competing risks data: An application to study patient-ventilator asynchronies in critical care …

2017

Mechanical ventilation is a common procedure of life support in intensive care. Patient-ventilator asynchronies (PVAs) occur when the timing of the ventilator cycle is not simultaneous with the timing of the patient respiratory cycle. The association between severity markers and the events death or alive discharge has been acknowledged before, however, little is known about the addition of PVAs data to the analyses. We used an index of asynchronies (AI) to measure PVAs and the SOFA (sequential organ failure assessment) score to assess overall severity. To investigate the added value of including the AI, we propose a Bayesian joint model of bivariate longitudinal and competing risks data. Th…

Spatio-Temporal Modeling of Zika and Dengue Infections within Colombia

2018

The aim of this study is to estimate the parallel relative risk of Zika virus disease (ZVD) and dengue using spatio-temporal interaction effects models for one department and one city of Colombia during the 2015&ndash

Pleistocene allopatric differentiation followed by recent range expansion explains the distribution and molecular diversity of two congeneric crustac…

2021

AbstractPleistocene glaciations had a tremendous impact on the biota across the Palaearctic, resulting in strong phylogeographic signals of range contraction and rapid postglacial recolonization of the deglaciated areas. Here, we explore the diversity patterns and history of two sibling species of passively dispersing taxa typical of temporary ponds, fairy shrimps (Anostraca). We combine mitochondrial (COI) and nuclear (ITS2 and 18S) markers to conduct a range-wide phylogeographic study including 56 populations of Branchinecta ferox and Branchinecta orientalis in the Palaearctic. Specifically, we investigate whether their largely overlapping ranges in Europe resulted from allopatric differe…

S. Typhimurium virulence changes caused by exposure to different non-thermal preservation treatments using C. elegans

2017

The aims of this research study were: (i) to postulate Caenorhabditis elegans (C. elegans) as a useful organism to describe infection by Salmonella enterica serovar Typhimurium (S. Typhimurium), and (ii) to evaluate changes in virulence of S. Typhimurium when subjected repetitively to different antimicrobial treatments. Specifically, cauliflower by-product infusion, High Hydrostatic Pressure (HHP), and Pulsed Electric Fields (PEF). This study was carried out by feeding C. elegans with different microbial populations: E. coli OP50 (optimal conditions), untreated S. Typhimurium, S. Typhimurium treated once and three times with cauliflower by-product infusion, S. Typhimurium treated once and f…

“Anti-Bayesian” flat and hierarchical clustering using symmetric quantiloids

2017

A myriad of works has been published for achieving data clustering based on the Bayesian paradigm, where the clustering sometimes resorts to Naive-Bayes decisions. Within the domain of clustering, the Bayesian principle corresponds to assigning the unlabelled samples to the cluster whose mean (or centroid) is the closest. Recently, Oommen and his co-authors have proposed a novel, counter-intuitive and pioneering PR scheme that is radically opposed to the Bayesian principle. The rational for this paradigm, referred to as the “Anti-Bayesian” (AB) paradigm, involves classification based on the non-central quantiles of the distributions. The first-reported work to achieve clustering using the A…

Discretized Bayesian Pursuit – A New Scheme for Reinforcement Learning

2012

Published version of a chapter in the book: Advanced Research in Applied Artificial Intelligence. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-31087-4_79 The success of Learning Automata (LA)-based estimator algorithms over the classical, Linear Reward-Inaction ( L RI )-like schemes, can be explained by their ability to pursue the actions with the highest reward probability estimates. Without access to reward probability estimates, it makes sense for schemes like the L RI to first make large exploring steps, and then to gradually turn exploration into exploitation by making progressively smaller learning steps. However, this behavior becomes counter-intuitive wh…

Solving Non-Stationary Bandit Problems by Random Sampling from Sibling Kalman Filters

2010

Published version of an article from Lecture Notes in Computer Science. Also available at SpringerLink: http://dx.doi.org/10.1007/978-3-642-13033-5_21 The multi-armed bandit problem is a classical optimization problem where an agent sequentially pulls one of multiple arms attached to a gambling machine, with each pull resulting in a random reward. The reward distributions are unknown, and thus, one must balance between exploiting existing knowledge about the arms, and obtaining new information. Dynamically changing (non-stationary) bandit problems are particularly challenging because each change of the reward distributions may progressively degrade the performance of any fixed strategy. Alt…

Thompson Sampling Guided Stochastic Searching on the Line for Adversarial Learning

2015

The multi-armed bandit problem has been studied for decades. In brief, a gambler repeatedly pulls one out of N slot machine arms, randomly receiving a reward or a penalty from each pull. The aim of the gambler is to maximize the expected number of rewards received, when the probabilities of receiving rewards are unknown. Thus, the gambler must, as quickly as possible, identify the arm with the largest probability of producing rewards, compactly capturing the exploration-exploitation dilemma in reinforcement learning. In this paper we introduce a particular challenging variant of the multi-armed bandit problem, inspired by the so-called N-Door Puzzle. In this variant, the gambler is only tol…