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pro vyhledávání: '"A, Martínez Rubio"'
In this work, we analyze two of the most fundamental algorithms in geodesically convex optimization: Riemannian gradient descent and (possibly inexact) Riemannian proximal point. We quantify their rates of convergence and produce different variants w
Externí odkaz:
http://arxiv.org/abs/2403.10429
Autor:
Serrano, Sergio, Barrio, Roberto, Martínez-Rubio, Álvaro, Belmonte-Beitia, Juan, Pérez-García, Víctor M.
Chimeric Antigen Receptor T (CAR-T) cell therapy has been proven to be successful against different leukaemias and lymphomas. This paper makes an analytical and numerical study of a mathematical model describing the competition of CAR-T, leukaemias t
Externí odkaz:
http://arxiv.org/abs/2403.00340
Convex curvature properties are important in designing and analyzing convex optimization algorithms in the Hilbertian or Riemannian settings. In the case of the Hilbertian setting, strongly convex sets are well studied. Herein, we propose various def
Externí odkaz:
http://arxiv.org/abs/2312.03583
Publikováno v:
Proceedings of Thirty Sixth Conference on Learning Theory (COLT 2023): https://proceedings.mlr.press/v195/criscitiello23b.html
Let $f \colon \mathcal{M} \to \mathbb{R}$ be a Lipschitz and geodesically convex function defined on a $d$-dimensional Riemannian manifold $\mathcal{M}$. Does there exist a first-order deterministic algorithm which (a) uses at most $O(\mathrm{poly}(d
Externí odkaz:
http://arxiv.org/abs/2307.12743
Autor:
Cristina Escamilla-Robla, Elisa Giménez-Fita, Natura Colomer-Pérez, David Martínez-Rubio, Jaime Navarrete
Publikováno v:
European Journal of Psychology Applied to Legal Context, Vol 16, Iss 2, Pp 87-96 (2024)
Background/Aim: The number of convictions related to crimes against road safety continues to increase, with more than half being caused by driving under the influence (DUI) of alcohol or drugs. In Spain, offenders for crimes against road safety have
Externí odkaz:
https://doaj.org/article/28d01b1c982c40a28136ecaf42f246b8
In this work, we study optimization problems of the form $\min_x \max_y f(x, y)$, where $f(x, y)$ is defined on a product Riemannian manifold $\mathcal{M} \times \mathcal{N}$ and is $\mu_x$-strongly geodesically convex (g-convex) in $x$ and $\mu_y$-s
Externí odkaz:
http://arxiv.org/abs/2305.16186
It has recently been shown that ISTA, an unaccelerated optimization method, presents sparse updates for the $\ell_1$-regularized personalized PageRank problem, leading to cheap iteration complexity and providing the same guarantees as the approximate
Externí odkaz:
http://arxiv.org/abs/2303.12875
Publikováno v:
BMC Oral Health, Vol 24, Iss 1, Pp 1-8 (2024)
Abstract Background The purpose of this study was to test how musical flow using baroque (BM) and classical era music (CM) as a non-pharmacological therapy can control anxiety and pain levels among patients undergoing IPI (Immediate post-extraction i
Externí odkaz:
https://doaj.org/article/1f3b4b0e1ef74819962bc6cf96e26de4
Autor:
Aleix Olivella, Luis Almenar‐Bonet, Pedro Moliner, Emmanuel Coloma, Antoni Martínez‐Rubio, Marco Paz Bermejo, Ramon Boixeda, German Cediel, Ana Belén Méndez Fernández, Lorenzo Facila Rubio
Publikováno v:
ESC Heart Failure, Vol 11, Iss 2, Pp 628-636 (2024)
Abstract Worsening heart failure (HF) is a vulnerable period in which the patient has a markedly high risk of death or HF hospitalization (up to 10% and 30%, respectively, within the first weeks after episode). The prognosis of HF patients can be imp
Externí odkaz:
https://doaj.org/article/fd3fc4ba948d4bd3b9b3019a4111c49a
We propose a globally-accelerated, first-order method for the optimization of smooth and (strongly or not) geodesically-convex functions in a wide class of Hadamard manifolds. We achieve the same convergence rates as Nesterov's accelerated gradient d
Externí odkaz:
http://arxiv.org/abs/2211.14645