Zobrazeno 1 - 10
of 482
pro vyhledávání: '"Matey, P"'
Autor:
Prasadan, Akshay, Neykov, Matey
We obtain the minimax rate for a mean location model with a bounded star-shaped set $K \subseteq \mathbb{R}^n$ constraint on the mean, in an adversarially corrupted data setting with Gaussian noise. We assume an unknown fraction $\epsilon<1/2-\kappa$
Externí odkaz:
http://arxiv.org/abs/2412.03832
Autor:
Prasadan, Akshay, Neykov, Matey
We consider a convex constrained Gaussian sequence model and characterize necessary and sufficient conditions for the least squares estimator (LSE) to be optimal in a minimax sense. For a closed convex set $K\subset \mathbb{R}^n$ we observe $Y=\mu+\x
Externí odkaz:
http://arxiv.org/abs/2406.05911
Semi-supervised datasets are ubiquitous across diverse domains where obtaining fully labeled data is costly or time-consuming. The prevalence of such datasets has consistently driven the demand for new tools and methods that exploit the potential of
Externí odkaz:
http://arxiv.org/abs/2402.18921
Autor:
Prasadan, Akshay, Neykov, Matey
We quantify the minimax rate for a nonparametric regression model over a convex function class $\mathcal{F}$ with bounded diameter. We obtain a minimax rate of ${\varepsilon^{\ast}}^2\wedge\mathrm{diam}(\mathcal{F})^2$ where \[\varepsilon^{\ast} =\su
Externí odkaz:
http://arxiv.org/abs/2401.07968
Autor:
Abraham Tettey-Matey, Viola Donati, Chiara Cimmino, Chiara Di Pietro, Damiano Buratto, Mariateresa Panarelli, Alberto Reale, Arianna Calistri, Maria Vittoria Fornaini, Ruhong Zhou, Guang Yang, Francesco Zonta, Daniela Marazziti, Fabio Mammano
Publikováno v:
Cell Communication and Signaling, Vol 22, Iss 1, Pp 1-18 (2024)
Abstract Connexins (Cxs) are fundamental in cell–cell communication, functioning as gap junction channels (GJCs) that facilitate solute exchange between adjacent cells and as hemichannels (HCs) that mediate solute exchange between the cytoplasm and
Externí odkaz:
https://doaj.org/article/b229756db10d4abb859284512f10f9bb
Autor:
Neykov, Matey
This paper is concerned with signal detection in Gaussian noise under quadratically convex orthosymmetric (QCO) constraints. Specifically the null hypothesis assumes no signal, whereas the alternative considers signal which is separated in Euclidean
Externí odkaz:
http://arxiv.org/abs/2308.13036
This paper is concerned with minimax conditional independence testing. In contrast to some previous works on the topic, which use the total variation distance to separate the null from the alternative, here we use the Wasserstein distance. In additio
Externí odkaz:
http://arxiv.org/abs/2308.08672
This paper is concerned with the problem of conditional independence testing for discrete data. In recent years, researchers have shed new light on this fundamental problem, emphasizing finite-sample optimality. The non-asymptotic viewpoint adapted i
Externí odkaz:
http://arxiv.org/abs/2308.05373
Autor:
Alberto González-Pérez, Laura Diaz-Sanahuja, Miguel Matey-Sanz, Jorge Osma, Carlos Granell, Juana Bretón-López, Sven Casteleyn
Publikováno v:
Digital Health, Vol 10 (2024)
Objective While exposure therapy (ET) has the potential to help people tolerate intense situation-specific emotions and change avoidance behaviours, no smartphone solution exists to guide the process of in-vivo ET. A geolocation-based smartphone soft
Externí odkaz:
https://doaj.org/article/71b27486a7a942e29179a460abb71029
Autor:
Shrotriya, Shamindra, Neykov, Matey
We study the classical problem of deriving minimax rates for density estimation over convex density classes. Building on the pioneering work of Le Cam (1973), Birge (1983, 1986), Wong and Shen (1995), Yang and Barron (1999), we determine the exact (u
Externí odkaz:
http://arxiv.org/abs/2210.11436