Learning how to be robust: Deep polynomial regression

Polynomial regression is a recurrent problem with a large number of applications. In computer vision it often appears in motion analysis. Whatever the application, standard methods for regression of polynomial models tend to deliver biased results when the input data is heavily contaminated by outliers. Moreover, the problem is even harder when outliers have strong structure. Departing from problem-tailored heuristics for robust estimation of parametric models, we explore deep convolutional neural networks. Our work aims to find a generic approach for training deep regression models without the explicit need of supervised annotation. We bypass the need for a tailored loss function on the regression parameters by attaching to our model a differentiable hard-wired decoder corresponding to the polynomial operation at hand. We demonstrate the value of our findings by comparing with standard robust regression methods. Furthermore, we demonstrate how to use such models for a real computer vision problem, i.e., video stabilization. The qualitative and quantitative experiments show that neural networks are able to learn robustness for general polynomial regression, with results that well overpass scores of traditional robust estimation methods.Comment: 18 pages, conferenc

Generalization of the concepts of seniority number and ionicity

We present generalized versions of the concepts of seniority number and ionicity. These generalized numbers count respectively the partially occupied and fully occupied shells for any partition of the orbital space into shells. The Hermitian operators whose eigenspaces correspond to wave functions of definite generalized seniority or ionicity values are introduced. The generalized seniority numbers (GSNs) afford to establish refined hierarchies of configuration interaction (CI) spaces within those of fixed ordinary seniority. Such a hierarchy is illustrated on the buckminsterfullerene molecule

The Missing Data Encoder: Cross-Channel Image Completion\\with Hide-And-Seek Adversarial Network

Image completion is the problem of generating whole images from fragments only. It encompasses inpainting (generating a patch given its surrounding), reverse inpainting/extrapolation (generating the periphery given the central patch) as well as colorization (generating one or several channels given other ones). In this paper, we employ a deep network to perform image completion, with adversarial training as well as perceptual and completion losses, and call it the ``missing data encoder'' (MDE). We consider several configurations based on how the seed fragments are chosen. We show that training MDE for ``random extrapolation and colorization'' (MDE-REC), i.e. using random channel-independent fragments, allows a better capture of the image semantics and geometry. MDE training makes use of a novel ``hide-and-seek'' adversarial loss, where the discriminator seeks the original non-masked regions, while the generator tries to hide them. We validate our models both qualitatively and quantitatively on several datasets, showing their interest for image completion, unsupervised representation learning as well as face occlusion handling

Changes in the nutritional status of Bolivian women 1994-1998: demographic and social predictors

Introduction: Bolivia, as one of the poorest Latin American countries, has dealt with the problems of undernutrition for the last 50 y. Little importance has been given to the increase in overweight and obesity among the population, despite the scientific evidence linking overweight and obesity with mortality and morbidity. Objective: To describe the social and demographic determinants of the nutritional status among women in Bolivia between 1989 and 1998 to gain a better understanding of the nutrition transition phenomena and to identify urgent research needs. Methodology: Secondary analysis of the raw data of the Bolivian National Demographic and Health Surveys of 1994 and 1998. Changes in the prevalence of underweight, obesity and overweight are described by sociodemographic characteristics of Bolivian women. Social and demographic determinants of nutritional status have been fitted into a logistic model. Results: The prevalence of overweight (defined as 25 less than or equal to BMI < 30 kg/m(2)) among women of reproductive age (20-44 y) increased by 9 percentage points between 1994 and 1998 (P < 0.001), while the prevalence of normal BMI decreased by 10 percentage points (P < 0.001). The decrease in the prevalence of underweight (defined as BMI <18.5 kg/m(2)) from 2.4% in 1994 to less than 1% in 1998 was statistically significant (P < 0.001). Obesity (defined as BMI &GE;30 kg/m(2)) was positively associated with geographical region (P = 0.001), educational level (P < 0.001), age (P = 0.003) and total number of children (P = 0.001) and negatively associated to rural locality (P = 0.001) and native languages(P < 0.001). Overweight was inversely associated with rural locality (P = 0.013) and with Quechua language (P = 0.04), while the total number of children (P < 0.001) and year of survey (P < 0.001) were positively associated. Underweight decreased dramatically (P < 0.001), being positively associated with the region of residence (P = 0.04) and inversely associated with the total number of children (P = 0.006). Conclusion: The present study suggests that the population of Bolivia is in a transitional stage, with overweight becoming as much of a problem as undernutrition

Hybrid multi-layer Deep CNN/Aggregator feature for image classification

Deep Convolutional Neural Networks (DCNN) have established a remarkable performance benchmark in the field of image classification, displacing classical approaches based on hand-tailored aggregations of local descriptors. Yet DCNNs impose high computational burdens both at training and at testing time, and training them requires collecting and annotating large amounts of training data. Supervised adaptation methods have been proposed in the literature that partially re-learn a transferred DCNN structure from a new target dataset. Yet these require expensive bounding-box annotations and are still computationally expensive to learn. In this paper, we address these shortcomings of DCNN adaptation schemes by proposing a hybrid approach that combines conventional, unsupervised aggregators such as Bag-of-Words (BoW), with the DCNN pipeline by treating the output of intermediate layers as densely extracted local descriptors. We test a variant of our approach that uses only intermediate DCNN layers on the standard PASCAL VOC 2007 dataset and show performance significantly higher than the standard BoW model and comparable to Fisher vector aggregation but with a feature that is 150 times smaller. A second variant of our approach that includes the fully connected DCNN layers significantly outperforms Fisher vector schemes and performs comparably to DCNN approaches adapted to Pascal VOC 2007, yet at only a small fraction of the training and testing cost.Comment: Accepted in ICASSP 2015 conference, 5 pages including reference, 4 figures and 2 table

Personal relatedness and attachment in infants of mothers with borderline personality disorder

The principal aim of this study was to assess personal relatedness and attachment patterns in 12-month-old infants of mothers with borderline personality disorder (BPD). We also evaluated maternal intrusive insensitivity toward the infants in semistructured play. We videotaped 10 mother-infant dyads with borderline mothers and 22 dyads where the mothers were free from psychopathology, in three different settings: a modification of Winnicott's Set Situation in which infants faced an initially unresponsive ("still-face") stranger, who subsequently tried to engage the infant in a game of give and take; the Strange Situation of Ainsworth and Wittig; and a situation in which mothers were requested to teach their infants to play with miniature figures and a toy train. In relation to a set of a priori predictions, the results revealed significant group differences as follows: (a) compared with control infants, toward the stranger the infants of mothers with BPD showed lower levels of "availability for positive engagement," lower ratings of "behavior organization and mood state," and a lower proportion of interpersonally directed looks that were positive; (b) in the Strange Situation, a higher proportion (8 out of 10) of infants of borderline mothers were categorized as Disorganized; and (c) in play, mothers with BPD were rated as more "intrusively insensitive" toward their infants. The results are discussed in relation to hypotheses concerning the interpersonal relations of women with BPD, and possible implications for their infants' development

Investigation of friction hysteresis using a laboratory-scale tribometer

The current paper addresses the characterization of dynamic friction by using a laboratory-scale tribometer. A special post-processing script in MatLab has been developed in order to analyse the data from the experiments. A sine wave signal for the velocity is imposed, with three different frequencies and, consequently, acceleration and deceleration rates. A friction material from brakes, with nominal contact area of 254 mm², was subjected to sliding against a commercially available brake disc (gray cast iron, diameter of 256 mm). Some technical details and adjustments from the designed tribometer are showed and the results from the experiments are discussed. A friction hysteresis has been observed for all experimental curves, which exhibit loops in elliptical shape. A negative slope has been encountered for the curves when the imposed frequency is 1 Hz and 2 Hz, while for the highest frequency (4 Hz) the slope is positive. The laboratory-scale tribometer, associated to the post-processing stage, is capable to successfully be used to characterize friction hysteresis effect

Tribological behaviour of the low and high viscosity peek against steel using different contact pressures

In the market of polymers for tribological applications polyetheretherketone (PEEK) are often used for satisfying requests coming from industry regarding enhanced properties such as, thermal stability, friction and wear resistance. These properties promote the material to be used in so called high performance tribological applications. However, fundamental mechanisms governing friction and wear are not yet fully understood and neither is the influence of composition parameters. An important parameter is PEEK’s viscosity during manufacturing process which is heated up to semi-solid state, between its glass transition and melting temperature. This paper studies the friction and wear performance of low and high viscosity PEEK and pure PEEK under dry reciprocating sliding contact. The tests were performed in large scale specimens under flat-on-flat configuration to determine the transitions in tribological behaviour at different contact pressures. Tests were carried out at controlled atmosphere with 25 °C and a relative humidity of 50%. Contact pressures parameters were 4, 8 and 10 MPa used at a sliding speed of 20 mm/s. Post mortem analyses were carried out by means of 2-D surface topography and optical microscopy. The results show that the pure PEEK exhibits low coefficient of friction and wear rate when the contact pressure increase and similar behave for high and low viscosity PEEK

Anthropometry of height, weight, arm, wrist, abdominal circumference and body mass index, for Bolivian adolescents 12 to 18 years: Bolivian adolescent percentile values from the MESA study

Anthropometry is important as clinical tool for individual follow-up as well as for planning and health policy-making at population level. Recent references of Bolivian Adolescents are not available. The aim of this cross sectional study was to provide age and sex specific centile values and charts of Body Mass Index, height, weight, arm, wrist and abdominal circumference from Bolivian Adolescents. Data from the MEtabolic Syndrome in Adolescents (MESA) study was used. Thirty-two Bolivian clusters from urban and rural areas were selected randomly considering population proportions, 3445 school going adolescents, 12 to 18 y, 45% males; 55% females underwent anthropometric evaluation by trained personnel using standardized protocols for all interviews and examinations. Weight, height, wrist, arm and abdominal circumference data were collected. Body Mass Index was calculated. Smoothed age- and gender specific 3(rd), 5(th), 10(th), 25(th), 50(th) 75(th), 85(th), 90(th), 95(th) and 97(th) Bolivian adolescent percentiles(BAP) and Charts(BAC) where derived using LMS regression. Percentile-based reference data for the antropometrics of for Bolivian Adolescents are presented for the first time