National Research University – Higher School of Economics

About: National Research University – Higher School of Economics is a education organization based out in Moscow, Russia. It is known for research contribution in the topics: Population & Computer science. The organization has 12873 authors who have published 23376 publications receiving 256396 citations.

Après Nous Le Déluge: Fertility and the Intensity of Struggle against Immigration

Abstract: This paper is inspired by a puzzling empirical fact that despite the importance of controlling migration for their future, the host countries allocate very limited amounts of resources to the struggle against illegal immigration. The present model analyzes this issue in the context of low fertility in the host countries and suggests a novel channel though which the intensity of the struggle against immigration can be related to fertility. The analysis shows that for childless individuals, who have no reason to care about the future, it is optimal to contribute less to the costly immigration-prevention measures.

Universal Method for Stochastic Composite Optimization Problems

Abstract: A fast gradient method requiring only one projection is proposed for smooth convex optimization problems. The method has a visual geometric interpretation, so it is called the method of similar triangles (MST). Composite, adaptive, and universal versions of MST are suggested. Based on MST, a universal method is proposed for the first time for strongly convex problems (this method is continuous with respect to the strong convexity parameter of the smooth part of the functional). It is shown how the universal version of MST can be applied to stochastic optimization problems.

Generic and Specific Skills as Components of Human Capital: New Challenges for Education Theory and Practice

Abstract: Human capital theory in recent decades has become the basis for educational policy in many developed countries. Expert discussions, however, often undervalue research findings and developments related to this theory that since the 1970s have consistently enriched understanding of how human capital contributes to personal well-being and socioeconomic development of society as a whole. Educational policy lags behind these elaborations, which leads to a decline in the impact of education upon development worldwide. In the 21st century, fundamentally new trends in socioeconomic dynamics pose unprecedented challenges for educational systems around the world, including Russia. Despite the quantitative growth of money and time spent on education, performance per unit of education costs has fallen. The human potential, created by education, is facing more and more difficulties in its capitalization: economic growth is slowing down at both at the country level and globally. This situation brings to life new attempts to claim insignificance of education for economic growth and for individual success. So far, these attempts have not been very influential in educational policy, but in many countries, such arguments already serve as a backdrop for budget decisions that are detrimental for education. Educational systems need to complement practices that contribute to the development of human capital. In this regard, several theoretical elaborations that have not yet became part of the mainstream discussion on human capital, could be helpful for understanding the role of human capital in socioeconomic progress and possible ways to improve it in the short and long term.

Attribute-incremental construction of the canonical implication basis

Abstract: We propose a new algorithm constructing the canonical implication basis of a formal context. Being incremental, the algorithm processes a single attribute of the context at a single step. Experimental results bear witness to its competitiveness.

ZART: A Multifunctional Itemset Mining Algorithm

Abstract: In this paper, we present and detail a multifunctional itemset mining algorithm called Zart, which is based on the Pascal algorithm. Zart shows a number of additional features and performs the following, usually independent, tasks: identify frequent closed itemsets and associate generators to their closures. This makes Zart a complete algorithm for computing classes of itemsets including generators and closed itemsets. These characteristics allow one to extract minimal non-redundant association rules, a useful and lossless representation of association rules. In addition, being based on the Pascal algorithm, Zart has a rather efficient behavior on weakly and strongly correlated data. Accordingly, Zart is at the heart of the Coron platform, which is a domain independent, multi-purposed data mining platform, incorporating a rich collection of data mining algorithms.