Algorithms for simultaneous shrinkage and selection in regression and classification provide attractive solutions to knotty old statistical challenges. Nevertheless, as far as we can tell, Tibshirani’s Lasso algorithm has had little impact on statistical practice. Two particular reasons for this may be the relative inefficiency of the original Lasso algorithm and the relative complexity of more...

Accurate estimation of the spatio-temporal distribution snow water equivalent is essential given its global importance for understanding climate dynamics and change, as a source fresh water. Here, we explore potential using Long Short-Term Memory (LSTM) network continental regional scale modeling daily accumulation melt at 4-km pixel resolution across conterminous US (CONUS). To reduce training...

We propose a new basic trapdoor `IC (`-Invertible Cycles) of the mixed eld type forMultivariate Quadratic public key cryptosystems. This is the rst new basic trapdoor since the invention of Unbalanced Oil and Vinegar in 1997. `IC can be considered an extended form of the well-known Matsumoto-Imai Scheme A (also MIA or C∗), and share some features of stagewise triangular systems. However `IC has...

Subject. This article considers information and communication technologies as means of production necessary for the smooth functioning economic entities. Objectives. The aims to analyze changes in sales trend data importers manufacturers components development infrastructure. Methods. For study, we used regression equations based on panel by period volume. Results. finds that Russian companies ...

Finding sparse solutions to underdetermined inverse problems is a fundamental challenge encountered in a wide range of signal processing applications, from signal acquisition to source separation. Recent theoretical advances in our understanding of this problem have further increased interest in their application to various domains. In many areas, such as for example medical imaging or geophysi...

From the beginning of machine learning, rule induction has been regarded as one of the most important issues in this research area. One of the first rule induction algorithms was AQ introduced by Michalski in early 80’s. AQ, as well as several other well-known algorithms, such as CN2 and Ripper, are all based on sequential covering. With the advancement of machine learning, some new techniques ...

As machine learning algorithms enter applications in industrial settings, there is increased interest in controlling their cpu-time during testing. The cpu-time consists of the running time of the algorithm and the extraction time of the features. The latter can vary drastically when the feature set is diverse. In this paper, we propose an algorithm, the Greedy Miser, that incorporates the feat...

Alcohol­use disorders (AUD’s) commonly occur in people with other severe mental ill n esses, s uch as s chi zop h renia or bi p ola r d is order , and can exacerbate their psychiatric, medical, and family problems. Therefore, to improve detection of alcohol­ related problems, establish correct AUD diagnoses, and develop appropriate treatment plans, it is important to thoroughly assess severely ...

In this article an overview is given of traditional methodological approaches to stagewise cognitive developmental research. These approaches are evaluated and integrated on the basis of catastrophe theory. In particular, catastrophe theory specifies a set of common criteria for testing the discontinuity hypothesis proposed by Piaget. Separate criteria correspond to distinct methods used in cog...