LOGICAL ANALYSIS OF DATA WITH PARETO OPTIMAL PATTERNS SEARCH

Предлагается способ генерации логических закономерностей через аппроксимацию множества Парето эвристическим алгоритмом NSGA-II. Указанный метод применяется для решения задачи медицинской диагностики. The paper focuses on logical patterns generation as Pareto set approximation using heuristic algorithm NSGA-II. This method is used to solve the problem of medical diagnostics.

Almost sure central limit theorems in stochastic geometry

We prove an almost sure central limit theorem on the Poisson space, which is perfectly tailored for stabilizing functionals arising in stochastic geometry. As a consequence, we provide almost sure central limit theorems for (i) the total edge length of the k-nearest neighbors random graph, (ii) the clique count in random geometric graphs, and (iii) the volume of the set approximation via the Poisson–Voronoi tessellation.