12,018 research outputs found
On the Geometry of Message Passing Algorithms for Gaussian Reciprocal Processes
Reciprocal processes are acausal generalizations of Markov processes
introduced by Bernstein in 1932. In the literature, a significant amount of
attention has been focused on developing dynamical models for reciprocal
processes. Recently, probabilistic graphical models for reciprocal processes
have been provided. This opens the way to the application of efficient
inference algorithms in the machine learning literature to solve the smoothing
problem for reciprocal processes. Such algorithms are known to converge if the
underlying graph is a tree. This is not the case for a reciprocal process,
whose associated graphical model is a single loop network. The contribution of
this paper is twofold. First, we introduce belief propagation for Gaussian
reciprocal processes. Second, we establish a link between convergence analysis
of belief propagation for Gaussian reciprocal processes and stability theory
for differentially positive systems.Comment: 15 pages; Typos corrected; This paper introduces belief propagation
for Gaussian reciprocal processes and extends the convergence analysis in
arXiv:1603.04419 to the Gaussian cas
Mathematical modeling of local perfusion in large distensible microvascular networks
Microvessels -blood vessels with diameter less than 200 microns- form large,
intricate networks organized into arterioles, capillaries and venules. In these
networks, the distribution of flow and pressure drop is a highly interlaced
function of single vessel resistances and mutual vessel interactions. In this
paper we propose a mathematical and computational model to study the behavior
of microcirculatory networks subjected to different conditions. The network
geometry is composed of a graph of connected straight cylinders, each one
representing a vessel. The blood flow and pressure drop across the single
vessel, further split into smaller elements, are related through a generalized
Ohm's law featuring a conductivity parameter, function of the vessel cross
section area and geometry, which undergo deformations under pressure loads. The
membrane theory is used to describe the deformation of vessel lumina, tailored
to the structure of thick-walled arterioles and thin-walled venules. In
addition, since venules can possibly experience negative transmural pressures,
a buckling model is also included to represent vessel collapse. The complete
model including arterioles, capillaries and venules represents a nonlinear
system of PDEs, which is approached numerically by finite element
discretization and linearization techniques. We use the model to simulate flow
in the microcirculation of the human eye retina, a terminal system with a
single inlet and outlet. After a phase of validation against experimental
measurements, we simulate the network response to different interstitial
pressure values. Such a study is carried out both for global and localized
variations of the interstitial pressure. In both cases, significant
redistributions of the blood flow in the network arise, highlighting the
importance of considering the single vessel behavior along with its position
and connectivity in the network
On the Projective Geometry of Kalman Filter
Convergence of the Kalman filter is best analyzed by studying the contraction
of the Riccati map in the space of positive definite (covariance) matrices. In
this paper, we explore how this contraction property relates to a more
fundamental non-expansiveness property of filtering maps in the space of
probability distributions endowed with the Hilbert metric. This is viewed as a
preliminary step towards improving the convergence analysis of filtering
algorithms over general graphical models.Comment: 6 page
RISK AVERSION AND MAJOR CHOICE: EVIDENCE FROM ITALIAN STUDENTS
Does the choice of the field of study depend on individual risk aversion? The direction of the relationship between individual risk attitudes and type of college major chosen is potentially ambiguous. On the one hand, risk adverse individuals may prefer majors allowing high returns on the labour market; on the other hand, if these majors expose students to a higher probability of dropping out, those who are more risk adverse may be induced to choose less challenging fields. Using data from a sample of students enrolled in 2009 at a middle-sized Italian public University, we find that, controlling for a large number of individual characteristics, including cognitive abilities, personality traits and family background, more risk adverse students are more likely to choose any other field (Humanities, Engineering and Sciences) compared to Social Sciences. We interpret this result considering that some of these fields, such as Humanities, allow to reduce the risk of dropping out, while others (such as Engineering and Sciences)involve a lower risk on the labour market. It also emerges that the effect of risk aversion on major choice is related to student ability. Risk adverse students characterized by high abilities tend to prefer Engineering, while the propensity of risk adverse students to enrol in Humanities decreases when ability increases, suggesting that the attention paid to labour market risks and drop out risks varies according to student skills.Risk aversion, College choice, Education
Maximum Entropy Kernels for System Identification
A new nonparametric approach for system identification has been recently
proposed where the impulse response is modeled as the realization of a
zero-mean Gaussian process whose covariance (kernel) has to be estimated from
data. In this scheme, quality of the estimates crucially depends on the
parametrization of the covariance of the Gaussian process. A family of kernels
that have been shown to be particularly effective in the system identification
framework is the family of Diagonal/Correlated (DC) kernels. Maximum entropy
properties of a related family of kernels, the Tuned/Correlated (TC) kernels,
have been recently pointed out in the literature. In this paper we show that
maximum entropy properties indeed extend to the whole family of DC kernels. The
maximum entropy interpretation can be exploited in conjunction with results on
matrix completion problems in the graphical models literature to shed light on
the structure of the DC kernel. In particular, we prove that the DC kernel
admits a closed-form factorization, inverse and determinant. These results can
be exploited both to improve the numerical stability and to reduce the
computational complexity associated with the computation of the DC estimator.Comment: Extends results of 2014 IEEE MSC Conference Proceedings
(arXiv:1406.5706
Challenges for the Evaluation of the P.I.P.P.I. - Programme of Intervention for Prevention of Institutionalisation: between Partecipative and Experimental Pathways
Evaluation is constantly requested by governments and decision-makers, to prove that social policies and actions undertaken are effective in responding to problems. Also programmes contrasting child neglect are involved in such request to guarantee that children enjoy their childhood and ensure access to quality service. This paper focuses on an Italian evaluation experience of one such programme named the P.I.P.P.I. (Programme of Intervention for Prevention of Institutionalisation), the outcome of a collaboration between the University of Padua and the Italian Ministry of Welfare. The paper questions and challenges the experimental designs normally used for these evaluation purposes, highlighting how knowledge of effective treatments is far from the practices delivered. The study proposes an innovative evaluation path in which the participative evaluation, where the professionals build their own knowledge through an evaluation in the field, coexists with the choice of matching as a (quasi) experimental evaluation, responding to the Government\u2019s request for effective investments
P.I.P.P.I.: What has changed? How and why? The empirical evidence
This paper provides a summary of the results of the P.I.P.P.I. Program in achieving the prefixed goals on the final, intermediate and proximal outcome variables, regarding children\u2019s development, the positive exercise of parental competences and the effective action of services respectively. Therefore, the main purpose is to describe the impact of the program on the overall well-being of children and families in relation to the processes implemented. This is possible thanks to the wealth of information gathered by professionals through the tools provided for the analysis, design and monitoring activities in the work with families
The PEP Survey: evidence for intense star-forming activity in the majority of radio-selected AGN at z>~1
In order to investigate the FIR properties of radio-active AGN, we have
considered three different fields where both radio and FIR observations are the
deepest to-date: GOODS-South, GOODS-North and the Lockman Hole. Out of a total
of 92 radio-selected AGN, ~64% are found to have a counterpart in Herschel
maps. The percentage is maximum in the GOODS-North (72%) and minimum (~50%) in
the Lockman Hole, where FIR observations are shallower. Our study shows that in
all cases FIR emission is associated to star-forming activity within the host
galaxy. Such an activity can even be extremely intense, with star-forming rates
as high as ~10^3-10^4 Msun/yr. AGN activity does not inhibit star formation in
the host galaxy, just as on-site star-formation does not seem to affect AGN
properties, at least those detected at radio wavelengths and for z>~1.
Furthermore, physical properties such as the mass and age distributions of the
galaxies hosting a radio-active AGN do not seem to be affected by the presence
of an ongoing star-forming event. Given the very high rate of FIR detections,
we stress that this refers to the majority of the sample: most radio-active AGN
are associated with intense episodes of star-formation. However, the two
processes proceed independently within the same galaxy, at all redshifts but in
the local universe, where powerful enough radio activity reaches the necessary
strength to switch off the on-site star formation. Our data also show that for
z>~1 the hosts of radio-selected star-forming galaxies and AGN are
indistinguishable from each other both in terms of mass and IR luminosity
distributions. The two populations only differentiate in the very local
universe, whereby the few AGN which are still FIR-active are found in galaxies
with much higher masses and luminosities.Comment: 20 pages, 22 figures, to appear in MNRA
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