Zobrazeno 1 - 10
of 5 618
pro vyhledávání: '"P, Holtz"'
This paper addresses the problem of detecting points on or near the boundary of a dataset sampled, potentially with noise, from a compact manifold with boundary. We extend recent advances in doubly stochastic scaling of the Gaussian heat kernel via S
Externí odkaz:
http://arxiv.org/abs/2411.18942
We study a class of semi-linear differential Volterra equations with polynomial-type potentials that incorporates the effects of memory while being subjected to random perturbations via an additive Gaussian noise. We show that for a broad class of no
Externí odkaz:
http://arxiv.org/abs/2411.02459
Autor:
Glatt-Holtz, Nathan E., Holbrook, Andrew J., Krometis, Justin A., Mondaini, Cecilia F., Sheth, Ami
In the first edition of this Handbook, two remarkable chapters consider seemingly distinct yet deeply connected subjects ...
Comment: To appear in the Handbook of MCMC, 2nd Edition
Comment: To appear in the Handbook of MCMC, 2nd Edition
Externí odkaz:
http://arxiv.org/abs/2410.17398
Autor:
Jahani, Eaman, Manning, Benjamin S., Zhang, Joe, TuYe, Hong-Yi, Alsobay, Mohammed, Nicolaides, Christos, Suri, Siddharth, Holtz, David
In an online experiment with N = 1893 participants, we collected and analyzed over 18,000 prompts and over 300,000 images to explore how the importance of prompting will change as the capabilities of generative AI models continue to improve. Each par
Externí odkaz:
http://arxiv.org/abs/2407.14333
We study the minimization of a quadratic over Stiefel manifolds (the set of all orthogonal $r$-frames in \IR^n), which has applications in high-dimensional semi-supervised classification tasks. To reduce the computational complexity, sequential subsp
Externí odkaz:
http://arxiv.org/abs/2404.13301
There is substantial interest in the use of machine learning (ML)-based techniques throughout the electronic computer-aided design (CAD) flow, particularly methods based on deep learning. However, while deep learning methods have achieved state-of-th
Externí odkaz:
http://arxiv.org/abs/2403.00103
Autor:
Andrew Holtz, Johan Van Weyenbergh, Samuel L. Hong, Lize Cuypers, Áine O’Toole, Gytis Dudas, Marco Gerdol, Barney I. Potter, Francine Ntoumi, Claujens Chastel Mfoutou Mapanguy, Bert Vanmechelen, Tony Wawina-Bokalanga, Bram Van Holm, Soraya Maria Menezes, Katja Soubotko, Gijs Van Pottelbergh, Elke Wollants, Pieter Vermeersch, Ann-Sophie Jacob, Brigitte Maes, Dagmar Obbels, Veerle Matheeussen, Geert Martens, Jérémie Gras, Bruno Verhasselt, Wim Laffut, Carl Vael, Truus Goegebuer, Rob van der Kant, Frederic Rousseau, Joost Schymkowitz, Luis Serrano, Javier Delgado, Tom Wenseleers, Vincent Bours, Emmanuel André, Marc A. Suchard, Andrew Rambaut, Simon Dellicour, Piet Maes, Keith Durkin, Guy Baele
Publikováno v:
BMC Infectious Diseases, Vol 24, Iss 1, Pp 1-18 (2024)
Abstract We investigate the emergence, mutation profile, and dissemination of SARS-CoV-2 lineage B.1.214.2, first identified in Belgium in January 2021. This variant, featuring a 3-amino acid insertion in the spike protein similar to the Omicron vari
Externí odkaz:
https://doaj.org/article/e0f6914f63ac463b94c41b5682afba1e
Autor:
Brennan, Jennifer, Cong, Yahu, Yu, Yiwei, Lin, Lina, Peng, Yajun, Meng, Changping, Han, Ningren, Pouget-Abadie, Jean, Holtz, David
It is increasingly common in digital environments to use A/B tests to compare the performance of recommendation algorithms. However, such experiments often violate the stable unit treatment value assumption (SUTVA), particularly SUTVA's "no hidden tr
Externí odkaz:
http://arxiv.org/abs/2309.07107
Autor:
Holtz, Olga
Publikováno v:
Notices Amer. Math. Soc. 71 (2024), no. 6, 725-731
This short note for non-experts means to demystify the tasks of evaluating the Riemann Zeta Function at non-positive integers and at even natural numbers, both initially performed by Leonhard Euler. Treading in the footsteps of G. H. Hardy and others
Externí odkaz:
http://arxiv.org/abs/2308.11637
Motivated by the need to address the degeneracy of canonical Laplace learning algorithms in low label rates, we propose to reformulate graph-based semi-supervised learning as a nonconvex generalization of a \emph{Trust-Region Subproblem} (TRS). This
Externí odkaz:
http://arxiv.org/abs/2308.00142