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

Sparse and stable Markowitz portfolios

We consider the problem of portfolio selection within the classical Markowitz mean-variance framework, reformulated as a constrained least-squares regression problem. We propose to add to the objective function a penalty proportional to the sum of the absolute values of the portfolio weights. This penalty regularizes (stabilizes) the optimization problem, encourages sparse portfolios (i.e. portfolios with only few active positions), and allows to account for transaction costs. Our approach recovers as special cases the no-short-positions portfolios, but does allow for short positions in limited number. We implement this methodology on two benchmark data sets constructed by Fama and French. Using only a modest amount of training data, we construct portfolios whose out-of-sample performance, as measured by Sharpe ratio, is consistently and significantly better than that of the naive evenly-weighted portfolio which constitutes, as shown in recent literature, a very tough benchmark.Comment: Better emphasis of main result, new abstract, new examples and figures. New appendix with full details of algorithm. 17 pages, 6 figure

Замечания по вопросу о "Кугар"

This is where the abstract of this record would appear. This is only demonstration data

Using virtual reality in the training of security staff and evaluation of physical protection barriers in nuclear facilities

The physical security of facilities containing radioactive objects, an already important matter, now has a new aggravating factor: the existence of groups intending to obtain radioactive materials for the purpose of intentionally induce radioactive contamination incidents, as for example the explosion of dirty bombs in populated regions, damaging both people and environment. In this context, the physical security of such facilities must be reinforced so to reduce the possibilities of such incidents. This paper presents a adapted game engine used as a virtual reality system, enabling the modeling and simulation of scenarios of nuclear facilities containing radioactive objects. In these scenarios, the physical protection barriers, as fences and walls, are simulated along with vigilance screens. Using a computer network, several users can participate simultaneously in the simulation, being represented by avatars. Users can play the roles of both invaders and security staff. The invaders have as objective to surpass the facility’s physical protection barriers to steal radioactive objects and flee. The security staff have as objective to prevent and stop the theft of radioactive objects from the facility. The system can be used to analysis simulated scenarios and train vigilance/security staff. A test scenario was already developed and used, and the preliminary tests had satisfactory results, as they enabled the evaluation of the physical protection barriers of the virtual facility, and the training of those who participated in the simulations in the functions of a security staff

Effect of helium pre- or postconditioning on signal transduction kinases in patients undergoing coronary artery bypass graft surgery

Background: The noble gas helium induces pre- and postconditioning in animals and humans. Volatile anesthetics induce cardioprotection in humans undergoing coronary artery bypass graft (CABG) surgery. We hypothesized that helium induces pre-and postconditioning in CABG-patients, affecting signaling molecules protein kinase C-epsilon (PKC-epsilon), p38 mitogen activated protein kinase (p38 MAPK), extracellular signal-regulated kinase 1/2 (ERK-1/2) and heat shock protein 27 (HSP-27) within cardiac tissue, and reducing postoperative troponin levels. Methods: After ethical approval and informed consent, 125 elective patients undergoing CABG surgery were randomised into this prospective, placebo controlled, investigator blinded, parallel arm single-centre study. Helium preconditioning (3 x 5 min of 70 % helium and 30 % oxygen) was applied before aortic cross clamping; postconditioning (15 min of helium) was applied before release of the aortic cross clamp. Signaling molecules were measured in right atrial appendix specimens. Troponin-T was measured at 4, 12, 24 and 48 h postoperatively. Results: Baseline characteristics of all groups were similar. Helium preconditioning did not significantly alter the primary outcome (molecular levels of kinases PKC-e and HSP-27, ratio of activated p38 MAPK or ERK 1/2). Postoperative troponin T was 11 arbitrary units [5, 31; area-under-the-curve (interquartile range)] for controls, and no statistically significant changes were observed after helium preconditioning [He-pre: 11 (6, 18)], helium postconditioning [He-post: 11 (8, 15)], helium pre-and postconditioning [He-PP: 14 (6, 20)] and after sevoflurane preconditioning [APC: 12 (8, 24), p = 0.13]. No adverse effects related to study treatment were observed in this study. Conclusions: No effect was observed of helium preconditioning, postconditioning or the combination thereof on activation of p38 MAPK, ERK 1/2 or levels of HSP27 and PKC-e in the human heart. Helium pre-and postconditioning did not affect postoperative troponin release in patients undergoing CABG surgery

Traditional mixed linear modelling versus modern machine learning to estimate cow individual feed intake

Three modelling approaches were used to estimate cow individual feed intake(FI) using feeding trial data from a research farm, including weekly recordingsof milk production and composition, live-weight, parity, and total FI.Additionally, weather data (temperature, humidity) were retrieved from theDutch National Weather Service (KNMI). The 2014 data (245 cows; 277parities) were used for model development. The first model (M1) applied anexisting formula to estimate energy requirement using parity, fat and proteincorrected milk, and live-weight, and assumed this requirement to be equal toenergy intake and thus FI. The second model used ‘traditional’ Mixed LinearRegression, first using the same variables as in M1 as fixed effects (MLR1), andthen by adding weather data (MLR2). The third model applied BoostedRegression Tree, a ‘modern’ machine learning technique, again once with thesame variables as M1 (BRT1), and once with weather information added(BRT2). All models were validated on 2015 data (155 cows; 165 parities) usingcorrelation between estimated and actual FI to evaluate performance. BothMLRs had very high correlations (0.91) between actual and estimated FI on 2014data, much higher than 0.46 for M1, and 0.73 for both BRTs. When validated on2015 data, correlations dropped to 0.71 for MLR1 and 0.72 for MLR2, andincreased to 0.71 for M1 and 0.76 for both BRTs. FI estimated by BRT1 was, onaverage, 0.35kg less (range: -7.61 – 13.32kg) than actual FI compared to 0.52kgless (range: -11.67 – 19.87kg) for M1. Adding weather data did not improve FIestimations

Radiocarbon Chronologies and Extinction Dynamics of the Late Quaternary Mammalian Megafauna of the Taimyr Peninsula, Russian Federation

This paper presents 75 new radiocarbon dates based on late Quaternary mammal remains recovered from eastern Taimyr Peninsula and adjacent parts of the northern Siberian lowlands, Russian Federation, including specimens of woolly mammoth (Mammuthus primigenius), steppe bison (Bison priscus), muskox (Ovibos moschatus), moose (Alces alces), reindeer (Rangifer tarandus), horse (Equus caballus) and wolf (Canis lupus). New evidence permits reanalysis of megafaunal extinction dynamics in the Asian high Arctic periphery. Increasingly, radiometric records of individual species show evidence of a gap at or near the Pleistocene/Holocene boundary (PHB). In the past, the PHB gap was regarded as significant only when actually terminal, i.e., when it marked the apparent ‘‘last’’ occurrence of a species (e.g., current ‘‘last’’ occurrence date for woolly mammoth in mainland Eurasia is 9600 yr BP). However, for high Arctic populations of horses and muskoxen the gap marks an interruption rather than extinction, because their radiocarbon records resume, nearly simultaneously, much later in the Holocene. Taphonomic effects, ΔC14 flux, and biased sampling are unlikely explanations for these hiatuses. A possible explanation is that the gap is the signature of an event, of unknown nature, that prompted the nearly simultaneous crash of many megafaunal populations in the high Arctic and possibly elsewhere in Eurasia.

Future of the drug label:Perspectives from a multistakeholder dialogue

'Regulating drugs does not end when market access has been granted. Monitoring drugs over the life-cycle has become state of the art, inherent to evolving legislation and societal need. Here, we explore how the drug label could move along in a changing playing-field, and become a sustainable label for the future. A dialogue between academia, government, the pharmaceutical industry, and patient/societal organizations was organized by the Regulatory Science Network Netherlands, RSNN. This is their view.