Zobrazeno 1 - 10
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pro vyhledávání: '"Dalmasso, A. P."'
In this paper we introduce the John-Nirenberg's type spaces $\text{JN}_p$ associated with the Gaussian measure $d\gamma(x) = \pi^{-d/2}e^{-|x|^2}dx$ in $\mathbb{R}^d$ where $1
Externí odkaz:
http://arxiv.org/abs/2409.18354
We propose a test of the significance of a variable appearing on the Lasso path and use it in a procedure for selecting one of the models of the Lasso path, controlling the Family-Wise Error Rate. Our null hypothesis depends on a set A of already sel
Externí odkaz:
http://arxiv.org/abs/2409.02269
Autor:
Dalmasso, Nicolò, Calabrò, Antonello, Leethochawalit, Nicha, Vulcani, Benedetta, Boyett, Kristan, Trenti, Michele, Treu, Tommaso, Castellano, Marco, Bradač, Maruša, Metha, Benjamin, Santini, Paola
We present an analysis of the galaxy merger rate in the redshift range $4.0
Externí odkaz:
http://arxiv.org/abs/2403.11428
We report measurements of the galaxy two-point correlation function at cosmic dawn, using photometrically-selected sources from the JWST Advanced Deep Extragalactic Survey (JADES). The JWST/NIRCam dataset comprises approximately $N_g \simeq 7000$ pho
Externí odkaz:
http://arxiv.org/abs/2402.18052
We will show that, contrary to the behavior of the higher order Riesz transforms studied so far on the atomic Hardy space $\mathcal{H}^1(\mathbb R^n, \gamma)$, associated with the Ornstein-Uhlenbeck operator with respect to the $n$-dimensional Gaussi
Externí odkaz:
http://arxiv.org/abs/2402.05082
Autor:
Potluru, Vamsi K., Borrajo, Daniel, Coletta, Andrea, Dalmasso, Niccolò, El-Laham, Yousef, Fons, Elizabeth, Ghassemi, Mohsen, Gopalakrishnan, Sriram, Gosai, Vikesh, Kreačić, Eleonora, Mani, Ganapathy, Obitayo, Saheed, Paramanand, Deepak, Raman, Natraj, Solonin, Mikhail, Sood, Srijan, Vyetrenko, Svitlana, Zhu, Haibei, Veloso, Manuela, Balch, Tucker
Synthetic data has made tremendous strides in various commercial settings including finance, healthcare, and virtual reality. We present a broad overview of prototypical applications of synthetic data in the financial sector and in particular provide
Externí odkaz:
http://arxiv.org/abs/2401.00081
We present a novel approach for measuring the two-point correlation function of galaxies in narrow pencil beam surveys with varying depths. Our methodology is utilized to expand high-redshift galaxy clustering investigations up to $z \sim 8$ by analy
Externí odkaz:
http://arxiv.org/abs/2312.12329
Publikováno v:
Transformation Groups (2024)
We construct indefinite Einstein solvmanifolds that are standard, but not of pseudo-Iwasawa type. Thus, the underlying Lie algebras take the form $\mathfrak{g}\rtimes_D\mathbb{R}$, where $\mathfrak{g}$ is a nilpotent Lie algebra and $D$ is a nonsymme
Externí odkaz:
http://arxiv.org/abs/2312.03125
Autor:
Xiong, Zikai, Dalmasso, Niccolò, Sharma, Shubham, Lecue, Freddy, Magazzeni, Daniele, Potluru, Vamsi K., Balch, Tucker, Veloso, Manuela
Data distillation and coresets have emerged as popular approaches to generate a smaller representative set of samples for downstream learning tasks to handle large-scale datasets. At the same time, machine learning is being increasingly applied to de
Externí odkaz:
http://arxiv.org/abs/2311.05436
Autor:
Xiong, Zikai, Dalmasso, Niccolò, Mishler, Alan, Potluru, Vamsi K., Balch, Tucker, Veloso, Manuela
Recent years have seen a surge of machine learning approaches aimed at reducing disparities in model outputs across different subgroups. In many settings, training data may be used in multiple downstream applications by different users, which means i
Externí odkaz:
http://arxiv.org/abs/2311.00109