Search results for " Error."
showing 10 items of 1034 documents
A Bayesian Multilevel Random-Effects Model for Estimating Noise in Image Sensors
2020
Sensor noise sources cause differences in the signal recorded across pixels in a single image and across multiple images. This paper presents a Bayesian approach to decomposing and characterizing the sensor noise sources involved in imaging with digital cameras. A Bayesian probabilistic model based on the (theoretical) model for noise sources in image sensing is fitted to a set of a time-series of images with different reflectance and wavelengths under controlled lighting conditions. The image sensing model is a complex model, with several interacting components dependent on reflectance and wavelength. The properties of the Bayesian approach of defining conditional dependencies among parame…
Heretical Mutiple Importance Sampling
2016
Multiple Importance Sampling (MIS) methods approximate moments of complicated distributions by drawing samples from a set of proposal distributions. Several ways to compute the importance weights assigned to each sample have been recently proposed, with the so-called deterministic mixture (DM) weights providing the best performance in terms of variance, at the expense of an increase in the computational cost. A recent work has shown that it is possible to achieve a trade-off between variance reduction and computational effort by performing an a priori random clustering of the proposals (partial DM algorithm). In this paper, we propose a novel "heretical" MIS framework, where the clustering …
Unbiased Estimators and Multilevel Monte Carlo
2018
Multilevel Monte Carlo (MLMC) and unbiased estimators recently proposed by McLeish (Monte Carlo Methods Appl., 2011) and Rhee and Glynn (Oper. Res., 2015) are closely related. This connection is elaborated by presenting a new general class of unbiased estimators, which admits previous debiasing schemes as special cases. New lower variance estimators are proposed, which are stratified versions of earlier unbiased schemes. Under general conditions, essentially when MLMC admits the canonical square root Monte Carlo error rate, the proposed new schemes are shown to be asymptotically as efficient as MLMC, both in terms of variance and cost. The experiments demonstrate that the variance reduction…
Quantum Attacks on Classical Proof Systems - The Hardness of Quantum Rewinding
2014
Quantum zero-knowledge proofs and quantum proofs of knowledge are inherently difficult to analyze because their security analysis uses rewinding. Certain cases of quantum rewinding are handled by the results by Watrous (SIAM J Comput, 2009) and Unruh (Eurocrypt 2012), yet in general the problem remains elusive. We show that this is not only due to a lack of proof techniques: relative to an oracle, we show that classically secure proofs and proofs of knowledge are insecure in the quantum setting. More specifically, sigma-protocols, the Fiat-Shamir construction, and Fischlin's proof system are quantum insecure under assumptions that are sufficient for classical security. Additionally, we show…
Progressive Stochastic Binarization of Deep Networks
2019
A plethora of recent research has focused on improving the memory footprint and inference speed of deep networks by reducing the complexity of (i) numerical representations (for example, by deterministic or stochastic quantization) and (ii) arithmetic operations (for example, by binarization of weights). We propose a stochastic binarization scheme for deep networks that allows for efficient inference on hardware by restricting itself to additions of small integers and fixed shifts. Unlike previous approaches, the underlying randomized approximation is progressive, thus permitting an adaptive control of the accuracy of each operation at run-time. In a low-precision setting, we match the accu…
Fast Graph Filters for Decentralized Subspace Projection
2020
A number of inference problems with sensor networks involve projecting a measured signal onto a given subspace. In existing decentralized approaches, sensors communicate with their local neighbors to obtain a sequence of iterates that asymptotically converges to the desired projection. In contrast, the present paper develops methods that produce these projections in a finite and approximately minimal number of iterations. Building upon tools from graph signal processing, the problem is cast as the design of a graph filter which, in turn, is reduced to the design of a suitable graph shift operator. Exploiting the eigenstructure of the projection and shift matrices leads to an objective whose…
Thresholding projection estimators in functional linear models
2008
We consider the problem of estimating the regression function in functional linear regression models by proposing a new type of projection estimators which combine dimension reduction and thresholding. The introduction of a threshold rule allows to get consistency under broad assumptions as well as minimax rates of convergence under additional regularity hypotheses. We also consider the particular case of Sobolev spaces generated by the trigonometric basis which permits to get easily mean squared error of prediction as well as estimators of the derivatives of the regression function. We prove these estimators are minimax and rates of convergence are given for some particular cases.
Los emprendedores surgidos de las empresas multinacionales de inversión extranjera directa: un estudio exploratorio en Costa Rica
2014
ResumenEl presente trabajo busca evaluar la creación de empresas por parte de exempleados de empresas multinacionales de inversión extranjera directa. En concreto, se busca dimensionar el fenómeno, caracterizarlo, así como valorar el desempeño de las empresas creadas. El estudio se hizo mediante un muestreo aleatorio simple con margen de error del 7% y nivel de confianza del 95%, sobre una base de datos de 11.120 exempleados de empresas multinacionales en Costa Rica (n=175). Además se utilizó un grupo control ad hoc. Los resultados muestran cómo son estos emprendedores, el proceso creador experimentado, las características y el desempeño de las nuevas empresas.AbstractThe aim of this invest…
Thermal imaging ruled out as a supplementary assessment in patients with fibromyalgia: A cross-sectional study
2021
Background The diagnosis of fibromyalgia syndrome (FMS) syndrome is often complicated and relies on diagnostic criteria based mostly on the symptoms reported by patients. Implementing objective complementary tests would be desirable to better characterize this population. Objective The purpose of this cross-sectional study was to compare the skin temperature at rest using thermography in women with FMS and healthy women. Methods Eighty-six women with FMS and 92 healthy controls volunteered to participate. The temperature of all participants was measured by infra-red thermography, registering the skin surface temperature (minimum, maximum and average) at rest in different areas: neck, upper…
Estudio de perfiles evolutivos en la lectura. Validación y revisión del test individual de diagnóstico de errores en lectura (TIDEL)
2002
El propósito de esta tesis es doble: revisar y validar un instrumento observacional deerrores en lectura novedoso, el TIDEL (Secadas y Alfaro, 1998), analizando a su vez los datosaportados por este instrumento con relación al proceso evolutivo de la lectura. Para alcanzardicho objetivo se distinguen dos partes fundamentales. Una de revisión teórica en la que seincluye los capítulos destinados a:a) estudio a través de la base de datos educativa ERIC de términos utilizados enla investigación en lectura, así como de un estudio bibliométrico de laproductividad científica de autores y revistas en el Diagnóstico de la Lectura,b) revisión de los posicionamientos teóricos sobre el proceso lector, a…