Bayesian optimization using sequential Monte Carlo

We consider the problem of optimizing a real-valued continuous function $f$ using a Bayesian approach, where the evaluations of $f$ are chosen sequentially by combining prior information about $f$, which is described by a random process model, and past evaluation results. The main difficulty with this approach is to be able to compute the posterior distributions of quantities of interest which are used to choose evaluation points. In this article, we decide to use a Sequential Monte Carlo (SMC) approach

Multi-GPU maximum entropy image synthesis for radio astronomy

The maximum entropy method (MEM) is a well known deconvolution technique in radio-interferometry. This method solves a non-linear optimization problem with an entropy regularization term. Other heuristics such as CLEAN are faster but highly user dependent. Nevertheless, MEM has the following advantages: it is unsupervised, it has a statistical basis, it has a better resolution and better image quality under certain conditions. This work presents a high performance GPU version of non-gridding MEM, which is tested using real and simulated data. We propose a single-GPU and a multi-GPU implementation for single and multi-spectral data, respectively. We also make use of the Peer-to-Peer and Unified Virtual Addressing features of newer GPUs which allows to exploit transparently and efficiently multiple GPUs. Several ALMA data sets are used to demonstrate the effectiveness in imaging and to evaluate GPU performance. The results show that a speedup from 1000 to 5000 times faster than a sequential version can be achieved, depending on data and image size. This allows to reconstruct the HD142527 CO(6-5) short baseline data set in 2.1 minutes, instead of 2.5 days that takes a sequential version on CPU.Comment: 11 pages, 13 figure

On the Stability and the Approximation of Branching Distribution Flows, with Applications to Nonlinear Multiple Target Filtering

We analyse the exponential stability properties of a class of measure-valued equations arising in nonlinear multi-target filtering problems. We also prove the uniform convergence properties w.r.t. the time parameter of a rather general class of stochastic filtering algorithms, including sequential Monte Carlo type models and mean eld particle interpretation models. We illustrate these results in the context of the Bernoulli and the Probability Hypothesis Density filter, yielding what seems to be the first results of this kind in this subject

Correlations in weighted networks

We develop a statistical theory to characterize correlations in weighted networks. We define the appropriate metrics quantifying correlations and show that strictly uncorrelated weighted networks do not exist due to the presence of structural constraints. We also introduce an algorithm for generating maximally random weighted networks with arbitrary P(k,s) to be used as null models. The application of our measures to real networks reveals the importance of weights in a correct understanding and modeling of these heterogeneous systems

Surtsey and Mount St. Helens: a comparison of early succession rates

Surtsey and Mount St. Helens are celebrated but very different volcanoes. Permanent plots allow for comparisons that reveal mechanisms that control succession and its rate and suggest general principles. We estimated rates from structure development, species composition using detrended correspondence analysis (DCA), changes in Euclidean distance (ED) of DCA vectors, and by principal components analysis (PCA) of DCA. On Surtsey, rates determined from DCA trajectory analyses decreased as follows: gull colony on lava with sand > gull colony on lava, no sand ≫ lava with sand > sand spit > block lava > tephra. On Mount St. Helens, plots on lahar deposits near woodlands were best developed. The succession rates of open meadows declined as follows: <i>Lupinus</i>-dominated pumice > protected ridge with <i>Lupinus</i> > other pumice and blasted sites > isolated lahar meadows > barren plain. Despite the prominent contrasts between the volcanoes, we found several common themes. Isolation restricted the number of colonists on Surtsey and to a lesser degree on Mount St. Helens. Nutrient input from outside the system was crucial. On Surtsey, seabirds fashioned very fertile substrates, while on Mount St. Helens wind brought a sparse nutrient rain, then <i>Lupinus</i> enhanced fertility to promote succession. Environmental stress limits succession in both cases. On Surtsey, bare lava, compacted tephra and infertile sands restrict development. On Mount St. Helens, exposure to wind and infertility slow succession

Interregional mobility of talent in Spain: The role of job opportunities and qualities of places during the recent economic crisis

This paper seeks to extend our knowledge of the drivers behind talented workers’ mobility within the Spanish urban system and the patterns they may follow. For this purpose, the stock and flows of creative workers (selected on the basis of either the industry-based or occupational approaches) are studied at different spatial scales while also considering the influence of local characteristics as a source of attracting and retaining forces. The study is based on the analysis of a quite novel longitudinal micro-database from the Spanish Social Security office. Under the conditions of lower mobility of creative workers compared with other geographical contexts –a trend worsened by the economic crisis– we show that job opportunities, especially in connection with workers’ social networks, emerge as the most influential attracting factor. Thus, beyond the classic idea that agglomeration economies benefit all residents, we found evidence that the biggest cities, and Madrid in particular, had become “escalator regions”, propelling the careers of young creative workers that had been attracted to them. On the contrary, the influence of urban amenities seems limited to the retention of talent. This research aims to contribute to dealing with the challenge of upgrading local productive forces after the economic crisis and to develop tailor-made talent attraction and retention strategies.Fac. de Geografía e HistoriaTRUEMinisterio de Ciencia e Innovación (MICINN)/FEDERpu

On particle Gibbs Markov chain Monte Carlo models

This article analyses a new class of advanced particle Markov chain Monte Carlo algorithms recently introduced by Andrieu, Doucet, and Holenstein (2010). We present a natural interpretation of these methods in terms of well known unbiasedness properties of Feynman-Kac particle measures, and a new duality with many-body Feynman-Kac models. This perspective sheds a new light on the foundations and the mathematical analysis of this class of methods. A key consequence is the equivalence between the backward and ancestral particle Markov chain Monte Carlo methods, and Gibbs sampling of a many-body Feynman-Kac target distribution. Our approach also presents a new stochastic differential calculus based on geometric combinatorial techniques to derive explicit non-asymptotic Taylor type series of the semigroup of a class of particle Markov chain Monte Carlo models around their invariant measures with respect to the population size of the auxiliary particle sampler. These results provide sharp quan- titative estimates of the convergence properties of conditional particle Markov chain models with respect to the time horizon and the size of the systems. We illustrate the implication of these results with sharp estimates of the contraction coefficient and the Lyapunov exponent of conditional particle samplers, and explicit and non-asymptotic Lp-mean error decompositions of the law of the random states around the limiting invariant measure. The abstract framework developed in the article also allows the design of natural extensions to island (also called SMC2) type particle methodologies

FarmaTabac: una nueva experiencia antitabáquica

Diversos elementos nos hacen pronosticar que el farmacéutico comunitario tiene un porvenir importante de actuación profesional en el campo de la cesación tabáquica. El aumento de la presión social sobre los fumadores, derivada de la reciente modificación de la legislación sobre el tabaco, provocará, sin duda, un aumento de los intentos de cesación. La accesibilidad de los fumadores que intentan dejar el tabaco a los servicios especializados de salud es aún bastante limitada. La accesibilidad del farmacéutico comunitario, en cambio, es prácticamente universal. Es una ventaja que deberíamos aprovechar. La excesiva compartimentación del sistema sanitario, con circuitos demasiado rígidos, no siempre permite una atención adecuada. Con la experiencia FarmaTabac estamos explorando nuevos sistemas de comunicación para gestionar los casos de cesación tabáquica. El circuito habitual entre farmacéutico-paciente-médico es de carácter lineal, bastante lento y sin que exista coordinación entre los profesionales de la salud:Farmacéutico ↔ Paciente ↔ MédicoNuestra experiencia propone un modelo circular, más rápido e interactivo, que expondremos más adelante. Para ello, ha sido necesario realizar una reflexión colectiva sobre el problema del tabaquismo en toda su dimensión, más allá de la función profesional del farmacéutico comunitario. Las implicaciones económicas, sociales, sanitarias y de salud pública5 no permiten mantenerse en una supuesta neutralidad de la actuación profesional