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.

Entrepreneurship and Economic Growth: The Experience of Developed and Developing Countries

Abstract: This chapter elaborates on entrepreneurship in developed and developing countries and focuses on the optimization of entrepreneurial activities. Various scenarios are considered: independent functioning of the market, integration in the form of reorganization (mergers and acquisitions), integration in the form of clustering, and integration in the form of innovational networks and technological parks. The optimal structure of the integration processes and best-case scenarios for its implementation to accelerate the rate and increase the quality of economic growth are substantiated. The potential for uptake of integration processes in stimulating economic growth through entrepreneurship is determined by the level of institutionalization in an economy. In developed countries, all forms of company integration are characterized by the high level of institutionalization, which allows for their effective use for economic growth. Independent companies, mergers, and acquisitions restrain economic growth and reduce its quality, while clusters, technological parks, and innovational networks accelerate the rate of economic growth and increase its quality. In developing countries, integration processes in entrepreneurship have a different influence on economic growth and require further institutionalization.

Equivariant K-theory of Hilbert schemes via shuffle algebra

Abstract: In this paper we construct the action of Ding-Iohara and shuffle algebras on the sum of localized equivariant K-groups of Hilbert schemes of points on C2. We show that commutative elements Ki of shuffle algebra act through vertex operators over the positive part {hi}i>0 of the Heisenberg algebra in these K-groups. Hence we get an action of Heisenberg algebra itself. Finally, we normalize the basis of the structure sheaves of fixed points in such a way that it corresponds to the basis of Macdonald polynomials in the Fock space C[h1,h2,…].

f ( R ) constant-roll inflation

Abstract: The previously introduced class of two-parametric phenomenological inflationary models in general relativity in which the slow-roll assumption is replaced by the more general, constant-roll condition is generalized to the case of f(R) gravity. A simple constant-roll condition is defined in the original Jordan frame, and exact expressions for a scalaron potential in the Einstein frame, for a function f(R) (in the parametric form) and for inflationary dynamics are obtained. The region of the model parameters permitted by the latest observational constraints on the scalar spectral index and the tensor-to-scalar ratio of primordial metric perturbations generated during inflation is determined.

Additive regularization of topic models

Abstract: Probabilistic topic modeling of text collections has been recently developed mainly within the framework of graphical models and Bayesian inference. In this paper we introduce an alternative semi-probabilistic approach, which we call additive regularization of topic models (ARTM). Instead of building a purely probabilistic generative model of text we regularize an ill-posed problem of stochastic matrix factorization by maximizing a weighted sum of the log-likelihood and additional criteria. This approach enables us to combine probabilistic assumptions with linguistic and problem-specific requirements in a single multi-objective topic model. In the theoretical part of the work we derive the regularized EM-algorithm and provide a pool of regularizers, which can be applied together in any combination. We show that many models previously developed within Bayesian framework can be inferred easier within ARTM and in some cases generalized. In the experimental part we show that a combination of sparsing, smoothing, and decorrelation improves several quality measures at once with almost no loss of the likelihood.