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Articles by Alejandro Cholaquidis
Statistics > Machine Learning
[Submitted on 24 Apr 2026] Title:Concave Statistical Utility Maximization Bandits via Influence-Function Gradients View a PDF of the paper titled Concave Statistical Utility Maximization Bandits via Influence-Function Gradients, by Mat\'ias Carrasco and 1 other authors View PDF HTML (experimental) Abstract:We study stochastic multi-armed bandits in which the objective is a statistical functional of the long-run reward distribution, rather than expected reward alone.
New advances in set estimation
Resumen Some recent advances in Set Estimation, from 2009 to the present, are discussed. These include some new findings, improved convergence rates, and new type of sets under study. Typically, the theoretical results are derived under some shape constrains, such as -convexity or positive reach, which are briefly reviewed, together with some other new proposals in this line. Known constraints on the shape, such as -convexity and positive reach, as well as recently introduced ones are discussed.
Statistical analysis of measures of non-convexity
Alejandro Cholaquidis [1] ; Ricardo Fraiman [1] ; Leonardo Moreno [1] ; Beatriz Pateiro-López [2] [1] Universidad de la República, Montevideo, Uruguay [2] Universidade de Santiago de Compostela Localización: Test: An Official Journal of the Spanish Society of Statistics and Operations Research, ISSN-e 1863-8260, ISSN 1133-0686, Vol. 33, Nº. 1, 2024, págs.
A counter example on a Borsuk conjecture
Resumen The study of shape restrictions of subsets of Rd has several applications in many areas, being convexity, r-convexity, and positive reach, some of the most famous, and typically imposed in set estimation. The following problem was attributed to K. Borsuk, by J. Perkal in 1956:find an r-convex set which is not locally contractible. Stated in that way is trivial to find such a set.
Técnicas de teoría geométrica de la medida en estimación de conjuntos
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