The machine learning community has focused on confidentiality problems associated with statistical analyses that “integrate” data stored in multiple, distributed databases where there are barriers to simply integrating the databases. This paper discusses various techniques which can be used to perform statistical analysis for categorical data, especially in the form of log-linear analysis and l...

Random Fourier features is one of the most popular techniques for scaling up kernel methods, such as kernel ridge regression. However, despite impressive empirical results, the statistical properties of random Fourier features are still not well understood. In this paper we take steps toward filling this gap. Specifically, we approach random Fourier features from a spectral matrix approximation...

The main object of investigation in this paper is a very general regression model optional setting - when an observed process semimartingale depending on unknown parameter. It well-known that statistical data may present information flow/filtration without usual conditions. estimation problem achieved by means structural least squares (LS) estimates and their sequential versions. results the ar...

the survival of the firms depends on the adoption of techniques and methods for encouraging learning among people. on other hand, it is necessary to have an attitude for interaction and endeavour in order for the learning to be built and conserved. therefore, committed people in organizations have always been emphasized as a driving force of the extension and creation of learning. the aim of th...

[1] The main problem encountered when applying remote sensing and geographic information systems techniques for wildfire risk assessment is the necessity to integrate different data sources. The methods applied so far are usually based on regression techniques or on coefficients relying on experts’ knowledge. Hence fire managers are seeking an unbiased statistical model able to highlight the mu...