Search results for " metropoli"

Group Metropolis Sampling

2017

Monte Carlo (MC) methods are widely used for Bayesian inference and optimization in statistics, signal processing and machine learning. Two well-known class of MC methods are the Importance Sampling (IS) techniques and the Markov Chain Monte Carlo (MCMC) algorithms. In this work, we introduce the Group Importance Sampling (GIS) framework where different sets of weighted samples are properly summarized with one summary particle and one summary weight. GIS facilitates the design of novel efficient MC techniques. For instance, we present the Group Metropolis Sampling (GMS) algorithm which produces a Markov chain of sets of weighted samples. GMS in general outperforms other multiple try schemes…

Mens sana in corpore exhausto. Emociones y gestión de sí en escuelas secundarias del sur global

2020

In recent years, emotional education has become a central element in a series of guidelines on a global scale that have been translated into various state initiatives aimed at education. Thus, Mens sana in corpore exhausto proposes to demonstrate the tension that is expressed between the growing series of discourses on emotional education and the school climate and the exhaustive bodies of teachers and directors of public secondary schools in the Metropolitan Region of Buenos Aires (RMBA). By way of hypothesis, these policies are considered to work on the bodies of teachers and directors, encouraging them to continue and not stop under the logic of management and self-management that throw …

Prologo

2010

El área Metropolitana de Valencia en la crisis

2014

Se analiza el impacto económico, social y territorial de la crisis económica 2006-2011 en el Área Metropolitana de Valencia, tomada tanto como conjunto como en relación a su estructura interna. En este sentido, se concluye que la ciudad central, a pesar de estar perdiendo peso demográfico, parece resistir mejor que su entorno la embestida de la crisis, mientras que es la periferia más inmediata la más afectada por los problemas económicos, en particular por el aumento del desempleo.

El Vinalopó : una àrea metropolitana amb futur ?

2001

Josep.Sorribes@uv.es

Crisis económica y desarrollo metropolitano. Una propuesta de investigación

2015

[EN] The metropolitan areas have undergone deep transformations linked to neo-liberal globalization, whose effects have been disseminated with uneven intensity depending on their specific local paths. The current economic crisis and the austerity policies applied in the European periphery shows their contradictions and causes new social and spatial asymmetries that are best reflected in these large urban areas, modifying their development paths. This paper proposes an interpretation on the territorial dimension of the economic crisis, discusses some of its main metropolitan manifestations and proposes various lines of research. The effect of the financialisation in the production of urban s…

Group Importance Sampling for particle filtering and MCMC

2018

Bayesian methods and their implementations by means of sophisticated Monte Carlo techniques have become very popular in signal processing over the last years. Importance Sampling (IS) is a well-known Monte Carlo technique that approximates integrals involving a posterior distribution by means of weighted samples. In this work, we study the assignation of a single weighted sample which compresses the information contained in a population of weighted samples. Part of the theory that we present as Group Importance Sampling (GIS) has been employed implicitly in different works in the literature. The provided analysis yields several theoretical and practical consequences. For instance, we discus…

A Review of Multiple Try MCMC algorithms for Signal Processing

2018

Many applications in signal processing require the estimation of some parameters of interest given a set of observed data. More specifically, Bayesian inference needs the computation of {\it a-posteriori} estimators which are often expressed as complicated multi-dimensional integrals. Unfortunately, analytical expressions for these estimators cannot be found in most real-world applications, and Monte Carlo methods are the only feasible approach. A very powerful class of Monte Carlo techniques is formed by the Markov Chain Monte Carlo (MCMC) algorithms. They generate a Markov chain such that its stationary distribution coincides with the target posterior density. In this work, we perform a t…

Adaptive independent sticky MCMC algorithms

2018

In this work, we introduce a novel class of adaptive Monte Carlo methods, called adaptive independent sticky MCMC algorithms, for efficient sampling from a generic target probability density function (pdf). The new class of algorithms employs adaptive non-parametric proposal densities which become closer and closer to the target as the number of iterations increases. The proposal pdf is built using interpolation procedures based on a set of support points which is constructed iteratively based on previously drawn samples. The algorithm's efficiency is ensured by a test that controls the evolution of the set of support points. This extra stage controls the computational cost and the converge…

Grapham: Graphical models with adaptive random walk Metropolis algorithms

2008

Recently developed adaptive Markov chain Monte Carlo (MCMC) methods have been applied successfully to many problems in Bayesian statistics. Grapham is a new open source implementation covering several such methods, with emphasis on graphical models for directed acyclic graphs. The implemented algorithms include the seminal Adaptive Metropolis algorithm adjusting the proposal covariance according to the history of the chain and a Metropolis algorithm adjusting the proposal scale based on the observed acceptance probability. Different variants of the algorithms allow one, for example, to use these two algorithms together, employ delayed rejection and adjust several parameters of the algorithm…