Collaborative Hierarchical Sparse Modeling

Sparse modeling is a powerful framework for data analysis and processing. Traditionally, encoding in this framework is done by solving an l_1-regularized linear regression problem, usually called Lasso. In this work we first combine the sparsity-inducing property of the Lasso model, at the individual feature level, with the block-sparsity property of the group Lasso model, where sparse groups of features are jointly encoded, obtaining a sparsity pattern hierarchically structured. This results in the hierarchical Lasso, which shows important practical modeling advantages. We then extend this approach to the collaborative case, where a set of simultaneously coded signals share the same sparsity pattern at the higher (group) level but not necessarily at the lower one. Signals then share the same active groups, or classes, but not necessarily the same active set. This is very well suited for applications such as source separation. An efficient optimization procedure, which guarantees convergence to the global optimum, is developed for these new models. The underlying presentation of the new framework and optimization approach is complemented with experimental examples and preliminary theoretical results.Comment: To appear in CISS 201

N=2 Einstein-Yang-Mills' static two-center solutions

We construct bona fide one- and two-center supersymmetric solutions to N=2, d=4 supergravity coupled to SU(2) non-Abelian vector multiplets. The solutions describe black holes and global monopoles alone or in equilibrium with each other and exhibit non-Abelian hairs of different kinds.Comment: 46 pages, 1 figure; v2 references adde

Resolution of SU(2) monopole singularities by oxidation

We show how "colored" SU(2) BPS monopoles (that is: SU(2) monopoles satisfying the Bogomol'nyi equation whose Higgs field and magnetic charge vanish at infinity and which are singular at the origin) can be obtained from the BPST instanton by a singular dimensional reduction, explaining the origin of the singularity and implying that the singularity can be cured by the oxidation of the solution. We study the oxidation of other monopole solutions in this scheme.Comment: 13 pages, LaTeX file, no figure

Analysis of Gaussian Quadratic Forms with Application to Statistical Channel Modeling

Finalmente, en el contexto de modelado de canal, la metodología de análisis de variables propuesta permite obtener dos nuevas generalizaciones del conocido modelo de desvanecimiento kappa-mu shadowed. Estas dos nuevas distribuciones, nombradas Beckmann fluctuante y kappa-mu shadowed correlado, incluyen como casos particulares a la gran mayoría de distribuciones de desvanecimientos usadas en la literatura, abarcando desde los modelos clásicos de Rayleigh y Rice hasta otros más generales y complejos como el Beckmann y el kappa-mu. Para ambas distribuciones, se presenta su caracterización estadística de primer orden, i.e., función generadora de momentos (MGF), PDF y CDF; así como los estadísticos de segundo orden del modelo Beckmann fluctuante. Fecha de lectura de Tesis Doctoral: 24 Enero 2020En esta tesis se presenta una nueva aproximación a la distribución de de formas cuadráticas gaussianas (FCGs) no centrales tanto en variables reales como complejas. Para ello, se propone un nuevo método de análisis de variables aleatorias que, en lugar de centrarse en el estudio de la variable en cuestión, se basa en la caracterización estadística de una secuencia de variables aleatorias auxiliares convenientemente definida. Como consecuencia, las expresiones obtenidas, con independencia del grado de precisión adquirido, siempre representan una distribución válida, siendo ésta su principal ventaja. Aplicando este método, se obtienen simples expresiones recursivas para la función densidad de probabilidad (PDF) y la función de distribución (CDF) de las FCGs reales definidas positivas. En el caso de las formas complejas, esta nueva forma de análisis conduce a aproximaciones para los estadísticos de primer orden en términos de funciones elementales (exponenciales y potencias), siendo más convenientes para cálculos posteriores que otras soluciones disponibles en la literatura. La tratabilidad matemática se ejemplifica mediante el análisis de sistemas de combinación por razón máxima (MRC) sobre canales Rice correlados, proporcionando aproximaciones cerradas para la probabilidad de outage y la probabilidad de error de bit

Non-Abelian black holes in string theory

We study a family of 5-dimensional non-Abelian black holes that can be obtained by adding an instanton field to the well-known D1D5W Abelian black holes. Naively, the non-Abelian fields seem to contribute to the black-hole entropy but not to the mass due to their rapid fall-off at spatial infinity. By uplifting the 5-dimensional supergravity solution to 10-dimensional Heterotic Supergravity first and then dualizing it into a Type-I Supergravity solution, we show that the non-Abelian fields are associated to D5-branes dissolved into the D9-branes (dual to the Heterotic "gauge 5-branes") and that their associated RR charge does not, in fact, contribute to the entropy, which only depends on the number16 pages of D-strings and D5 branes and the momentum along the D-strings, as in the Abelian case. These "dissolved" or "gauge" D5-branes do contribute to the mass in the expected form. The correct interpretation of the 5-dimensional charges in terms of the string-theory objects solves the non-Abelian hair puzzle, allowing for the microscopic accounting of the entropy. We discuss the validity of the solution when alpha prime corrections are taken into account.Comment: Latex 2e file, 21 pages. A full appendix on alpha prime corrections and the corresponding discussions have been added. The conclusions have suffered minor changes. Version accepted in JHE

MEDEA: A DSGE Model for the Spanish Economy

In this paper, we provide a brief introduction to a new macroeconometric model of the Spanish economy named MEDEA (Modelo de Equilibrio Dinámico de la Economía EspañolA). MEDEA is a dynamic stochastic general equilibrium (DSGE) model that aims to describe the main features of the Spanish economy for policy analysis, counterfactual exercises, and forecasting. MEDEA is built in the tradition of New Keynesian models with real and nominal rigidities, but it also incorporates aspects such as a small open economy framework, an outside monetary authority such as the ECB, and population growth, factors that are important in accounting for aggregate fluctuations in Spain. The model is estimated with Bayesian techniques and data from the last two decades. Beyond describing the properties of the model, we perform different exercises to illustrate the potential of MEDEA, including historical decompositions, long-run and short-run simulations, and counterfactual experiments.DSGE Models, Likelihood Estimation, Bayesian Methods