Distributed statistical learning problems arise commonly when dealing with large datasets. In this setup, datasets are partitioned over machines, which compute locally, and communicate short messages. Communication is often the bottleneck. paper, we study one-step iterative weighted parameter averaging in linear models under data parallelism. We do regression on each machine, send results to a ...

The cloud model, which can implement uncertain transformation between a qualitative concept and its quantitative instantiations, has attracted great attentions in multi-criteria decision-making problems with linguistic information. This paper proposes some operations and a possibility degree of trapezium clouds as well as several new aggregation operators: the trapezium cloud weighted arithmeti...

We develop a new approach for decision making in educational management based on the use of distance measures. We focus on the selection of a studies plan from the perspective of an academic institution. We try to develop this approach showing the benefits of establishing an ideal plan that we compare with the available alternatives. We use the Minkowski distance, the ordered weighted averaging...

After briefly discussing several reasons for the energy balance closure problem in the surface layer, the paper focuses on the influence of the low frequency part of the turbulence spectrum on the residual. Changes in the turbulent fluxes in this part of the turbulence spectrum were found to have a significant influence on the changes of the residual. Using the ogive method, it was found that t...

In this paper we present two new types aggregation operators such as, induced Pythagorean fuzzy ordered weighted averaging aggregation operator and induced Pythagorean fuzzy hybrid averaging aggregation operator. We also discuss of important properties of these proposed operators and construct some examples to develop these operators.

Abstract An aggregation operator of linguistic interval-valued intuitionistic fuzzy numbers (LIVIFNs) is an important tool for solving cognitively inspired decision-making problems with LIVIFNs. So far, many operators LIVIFNs have been presented. Each these works well in its specific context. But they are not always monotone because their operational rules invariant and persistent. Dempster-Sha...

We develop a new approach for decision making with Dempster-Shafer theory of evidence by using uncertain information represented in the form of interval numbers. We suggest the use of different types of uncertain aggregation operators in the problem. Then, we obtain new aggregation operators such as the belief structure uncertain ordered weighted averaging (BSUOWA) operator and the BS uncertain...