2,748 research outputs found
Elastic-Net Regularization in Learning Theory
Within the framework of statistical learning theory we analyze in detail the
so-called elastic-net regularization scheme proposed by Zou and Hastie for the
selection of groups of correlated variables. To investigate on the statistical
properties of this scheme and in particular on its consistency properties, we
set up a suitable mathematical framework. Our setting is random-design
regression where we allow the response variable to be vector-valued and we
consider prediction functions which are linear combination of elements ({\em
features}) in an infinite-dimensional dictionary. Under the assumption that the
regression function admits a sparse representation on the dictionary, we prove
that there exists a particular ``{\em elastic-net representation}'' of the
regression function such that, if the number of data increases, the elastic-net
estimator is consistent not only for prediction but also for variable/feature
selection. Our results include finite-sample bounds and an adaptive scheme to
select the regularization parameter. Moreover, using convex analysis tools, we
derive an iterative thresholding algorithm for computing the elastic-net
solution which is different from the optimization procedure originally proposed
by Zou and HastieComment: 32 pages, 3 figure
Adaptive Kernel Methods Using the Balancing Principle
The regularization parameter choice is a fundamental problem in supervised learning since the performance of most algorithms crucially depends on the choice of one or more of such parameters. In particular a main theoretical issue regards the amount of prior knowledge on the problem needed to suitably choose the regularization parameter and obtain learning rates. In this paper we present a strategy, the balancing principle, to choose the regularization parameter without knowledge of the regularity of the target function. Such a choice adaptively achieves the best error rate. Our main result applies to regularization algorithms in reproducing kernel Hilbert space with the square loss, though we also study how a similar principle can be used in other situations. As a straightforward corollary we can immediately derive adaptive parameter choice for various kernel methods recently studied. Numerical experiments with the proposed parameter choice rules are also presented
PREDICTION MODELS FOR FREESTYLE PERFORMANCE TIMES IN MASTER SWIMMERS
This study was designed to define the most important factors to predict freestyle performance times in 135 elite master swimmers by prediction models which include age, anthropometric and strength variables. To cross validate these equations found for Elite swimmers, we used a group composed by 126 lower technical level age - and experience - matched master swimmers. Results demonstrated that age, height and hand grip strength were the best predictors in short events, whereas age and height predict middle and long events. The corresponding coefficients of determination (R2) of performance times were 0.84 in 50m, 0.73 in 100m, 0.75 in 200m, 0.66 in 400m and 0.63 in the 800m events. A good correlation have been found when these models have been applied in 126 non-elite master swimmers demonstrating to be useful in all Master swimmers
Understanding neural networks with reproducing kernel Banach spaces
Characterizing the function spaces corresponding to neural networks can
provide a way to understand their properties. In this paper we discuss how the theory
of reproducing kernel Banach spaces can be used to tackle this challenge. In particular, we prove a representer theorem for a wide class of reproducing kernel Banach
spaces that admit a suitable integral representation and include one hidden layer neural networks of possibly infinite width. Further, we show that, for a suitable class of
ReLU activation functions, the norm in the corresponding reproducing kernel Banach
space can be characterized in terms of the inverse Radon transform of a bounded real
measure, with norm given by the total variation norm of the measure. Our analysis
simplifies and extends recent results in [43, 34, 35]
Quality of life and psychosocial impacts of the different restrictive measures during one year into the COVID-19 pandemic on patients with cancer in Italy: An ecological study
Background: The aim of the study was to assess the perceived quality of life and the psychosocial impact of the various restrictive measures due to COVID-19 pandemic on cancer patients in Italy, as well as their perception of the relationship with doctors and caregivers. Methods: This study compares three population-based observational studies of patients with cancer carried out in three consecutive time periods characterized by different restrictive measures using a self-administered online questionnaire. Results: Among the basic needs, psychological and medical support appeared to be prevalent; so did the need for safe transportation to reach the treatment facilities. Internet was the main source of information on the coronavirus. Although 74.6% of the total number of patients did not give up hospital therapies, 34.8% complained about variations in the continuity of treatment, with different percentages in the three samples. The majority of the sample (73.8%) was worried of being infected, but 21.9% did not share their anxieties and worries with others. The multivariate regression analysis showed that a pessimistic perception of quality of life was influenced by living in extra-urban areas and alone (OR = 1.4; OR = 2.1); while a perception of a reduced physical function result affected by the state of anxiety and stress (OR = 1.9) and the difficulties in continuity of medical assistance (OR = 2.2). The scoring of the SF-12 in the Physical Component Summary and Mental Component Summary scores showed a fluctuating trend throughout the three periods investigated. Conclusions: It is important for health professionals, caregivers and social workers to identify the new needs in order to enhance home care interventions, personalize and optimize care, ensure continuity of care and guarantee a high quality of life even in a health emergency situation
Thymomas: a review.
Thymomas are neoplasma of thymic epithelial cells. They may be benign or malignant and may
associate with locai ìnvasiveness and paraneoplastic diseases. Myasthenia gravis is often
associated with thymomas, bui this is not thè rule. Several classifications have been proposed:
some of them follow thè histopathological findings (Rosai and Levine, Snover, Marino and Muller-
Hermelink classification), other emphasizes thè clinic-pathological stage (Masaoka, Verley and
Hollmann stadiation). One third of thymomas is asymptomatic. Diagnosis is made often by plain
X-ray and confirmed by Computed Tomography or fine needle biopsy. Surgery is effective in 100%
of noninvasive cases and in 58% of invasive ones. Radio and chemotherapy are recommended
only in advanced or inoperable stages
Cancer of the Thyroid in patients over the age of fifty.
Aim. The authors performed a retrospective investigation of
patients over thè age of 50, in order to detect any peculiarities of
cancer of thè thyroid possibly affecting surgical treatment and
whether age itself represented an independent prognostic factor.
Methods. A total of 152 patients were examined at thè Department
of Surgical Science of "La Sapienza" University of Rome
with a minimum follow- up of 10 years. The 152 subjects recruited
were divided into 3 age groups: from 51 to 60 years, (74 patients);
from 61 to 70 years, (57 patients); from 71 to 80 years, (21 patients).
Resulti. Relating thè different histologic types to age group, there
was found to be a lower incidence of well-differentiated carcinoma
and a relative increase in thè epidermoid and undifferentiated
forms in older patients. In thè 51-60 age group 80% of thè
patients were at stages I and II, while in thè 71-80 age group
56.2% of cases were at stages III and IV.
Conclusion. In thè elderly patient undifferentiated, anaplastic or
epidermoid forms and those with a higher biologica! aggressiveness
are more frequently found. We believe that prompt diagnosis
would present thè surgeon with neoplasms at an early stage
and with less aggressive histotypes, thus ensuring greater scope
for radicai surgical treatment and appreciably enhancing prognosis
Predictive equations not always overestimate the resting energy expenditure in amyotrophic lateral sclerosis patients
Fil: Libere, Guillermo P.. Centro del Parque; ArgentinaFil: Guastavino, Sabrina. Centro del Parque; ArgentinaFil: Escobar, Miguel A.. Centro del Parque; ArgentinaFil: de Vito, Eduardo. Centro del Parque; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay; Argentin
Measuring the magnetic axis alignment during solenoids working
A method for monitoring the misalignment of the magnetic axis in solenoids is proposed. This method
requires only a few measurements of the magnetic field at fixed positions inside the magnet aperture,
and thus overcomes the main drawback of sturdy moving mechanics of other Hall sensor-based
methods. Conversely to state-of-the-art axis determination, the proposed method can be applied also
during magnet operations, when the axis region and almost the whole remaining magnet aperture
are not accessible. Moreover, only a few measurements of the magnetic field at fixed positions inside
the magnet aperture are required: thus a slow process such as the mapping of the whole aperture of a
magnet by means of moving stages is not necessary. The mathematical formulation of the method is
explained, and a case study on a model of a multi–layer solenoid is presented. For this case study, the
uncertainty is assessed and the optimal placement of the Hall transducers is derived
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