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July 16, 2026
Team Success: Aligning Means with Objectives
In corporations, sports, and academia, people often face challenges they cannot handle alone. In such cases, selecting the right team is crucial. Tatiana Mayskaya, Associate Professor at the HSE Faculty of Economic Sciences and the International College of Economics and Finance, together with colleagues from foreign universities, examined team characteristics and found that less diverse teams are better suited to objectives where a high average performance is important, whereas more diverse teams are preferable when avoiding failure is critical. The paper has been published in Economic Theory.
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On Happy Colorings, Cuts, and Structural Parameterizations

P. 148–161.
Bliznets I., Sagunov D.

We study the Maximum Happy Vertices and Maximum Happy Edges problems. The former problem is a variant of clusterization, where some vertices have already been assigned to clusters. The second problem gives a natural generalization of Multiway Uncut, which is the complement of the classical Multiway Cut problem. Due to their fundamental role in theory and practice, clusterization and cut problems has always attracted a lot of attention. We establish a new connection between these two classes of problems by providing a reduction between Maximum Happy Vertices and Node Multiway Cut. Moreover, we study structural and distance to triviality parameterizations of Maximum Happy Vertices and Maximum Happy Edges. Obtained results in these directions answer questions explicitly asked in four works: Agrawal ’17, Aravind et al. ’16, Choudhari and Reddy ’18, Misra and Reddy ’17.

Language: English
DOI
Text on another site
Keywords: parameterized complexityHappy coloringHomophily lawClique-width

In book

Graph-Theoretic Concepts in Computer Science 45th International Workshop, WG 2019, Vall de Núria, Spain, June 19–21, 2019, Revised Papers
Bliznets I. Vol. 11789: Lecture Notes in Computer Science. , Springer, 2019.
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Computability and Complexity
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