Outliers can be particularly hard to detect, creating bias and inconsistency in the semi-parametric estimates. In this paper, we use Monte Carlo simulations demonstrate that methods, such as matching, are biased presence of outliers. Bad good leverage point outliers considered. Bias arises case bad points because they completely change distribution metrics used define counterfactuals; points, o...

in more recent years, it has become increasingly recognized that r&d; (research and development) is a key driver of economic growth, a source of innovation and change, and as such stimulates improvements in productivity and economic competitiveness. it is closely associated with knowledge and flexibility, two factors that have gained new significance as a source of competitiveness in an increas...

In this paper, we present an overview of generalized expectation criteria (GE), a simple, robust, scalable method for semi-supervised training using weakly-labeled data. GE fits model parameters by favoring models that match certain expectation constraints, such as marginal label distributions, on the unlabeled data. This paper shows how to apply generalized expectation criteria to two classes ...

Background & Aims: Tuberculosis is one of the most important diseases of century that involves all the human organs including lungs. Due to the yearly occurrence of 9 millions new cases and 1.5 millions deaths in the world, tuberculosis is in the center of attention. The aim of this study was to indentify factors affecting the time required for sputum smear conversion in patien...

Non-stationarity is ubiquitous in human behavior and addressing it the contextual bandits challenging. Several works have addressed problem by investigating semi-parametric warned that ignoring non-stationarity could harm performances. Another prevalent social interaction which has become available a form of network or graph structure. As result, graph-based received much attention. In this pap...

Finding non-Gaussian components of high-dimensional data is an important preprocessing step for efficient information processing. This article proposes a new linear method to identify the “nonGaussian subspace” within a very general semi-parametric framework. Our proposed method, called NGCA (non-Gaussian component analysis), is based on a linear operator which, to any arbitrary nonlinear (smoo...