Zobrazeno 1 - 10
of 11 102
pro vyhledávání: '"A, Palomar"'
In this paper, we present a novel optimization algorithm designed specifically for estimating state-space models to deal with heavy-tailed measurement noise and constraints. Our algorithm addresses two significant limitations found in existing approa
Externí odkaz:
http://arxiv.org/abs/2411.11320
Modern genomics research relies on genome-wide association studies (GWAS) to identify the few genetic variants among potentially millions that are associated with diseases of interest. Only reproducible discoveries of groups of associations improve o
Externí odkaz:
http://arxiv.org/abs/2410.05211
Genomics biobanks are information treasure troves with thousands of phenotypes (e.g., diseases, traits) and millions of single nucleotide polymorphisms (SNPs). The development of methodologies that provide reproducible discoveries is essential for th
Externí odkaz:
http://arxiv.org/abs/2410.05169
Autor:
d'Albenzio, Gabriella, Meng, Ruoyan, Aghayan, Davit, Pelanis, Egidijus, Hisey, Rebecca, Drejian, Sarkis, Fretland, Åsmund Avdem, Elle, Ole Jakob, Edwin, Bjørn, Palomar, Rafael
Objective: This study introduces a novel method for defining virtual resections in liver cancer surgery, aimed at enhancing the adaptability of parenchyma-sparing resection (PSR) plans. By comparing these with traditional anatomical resection (AR) pl
Externí odkaz:
http://arxiv.org/abs/2405.10960
This paper introduces Polynomial Graphical Lasso (PGL), a new approach to learning graph structures from nodal signals. Our key contribution lies in modeling the signals as Gaussian and stationary on the graph, enabling the development of a graph-lea
Externí odkaz:
http://arxiv.org/abs/2404.02621
Algorithms that ensure reproducible findings from large-scale, high-dimensional data are pivotal in numerous signal processing applications. In recent years, multivariate false discovery rate (FDR) controlling methods have emerged, providing guarante
Externí odkaz:
http://arxiv.org/abs/2401.15796
In high-dimensional data analysis, such as financial index tracking or biomedical applications, it is crucial to select the few relevant variables while maintaining control over the false discovery rate (FDR). In these applications, strong dependenci
Externí odkaz:
http://arxiv.org/abs/2401.15139
Learning a graph from data is the key to taking advantage of graph signal processing tools. Most of the conventional algorithms for graph learning require complete data statistics, which might not be available in some scenarios. In this work, we aim
Externí odkaz:
http://arxiv.org/abs/2312.16940
Weighted sum-rate (WSR) maximization plays a critical role in communication system design. This paper examines three optimization methods for WSR maximization, which ensure convergence to stationary points: two block coordinate ascent (BCA) algorithm
Externí odkaz:
http://arxiv.org/abs/2311.04546
Autor:
Tiffany A. Kosch, María Torres-Sánchez, H. Christoph Liedtke, Kyle Summers, Maximina H. Yun, Andrew J. Crawford, Simon T. Maddock, Md. Sabbir Ahammed, Victor L. N. Araújo, Lorenzo V. Bertola, Gary M. Bucciarelli, Albert Carné, Céline M. Carneiro, Kin O. Chan, Ying Chen, Angelica Crottini, Jessica M. da Silva, Robert D. Denton, Carolin Dittrich, Gonçalo Espregueira Themudo, Katherine A. Farquharson, Natalie J. Forsdick, Edward Gilbert, Jing Che, Barbara A. Katzenback, Ramachandran Kotharambath, Nicholas A. Levis, Roberto Márquez, Glib Mazepa, Kevin P. Mulder, Hendrik Müller, Mary J. O’Connell, Pablo Orozco-terWengel, Gemma Palomar, Alice Petzold, David W. Pfennig, Karin S. Pfennig, Michael S. Reichert, Jacques Robert, Mark D. Scherz, Karen Siu-Ting, Anthony A. Snead, Matthias Stöck, Adam M. M. Stuckert, Jennifer L. Stynoski, Rebecca D. Tarvin, Katharina C. Wollenberg Valero, The Amphibian Genomics Consortium
Publikováno v:
BMC Genomics, Vol 25, Iss 1, Pp 1-19 (2024)
Abstract Amphibians represent a diverse group of tetrapods, marked by deep divergence times between their three systematic orders and families. Studying amphibian biology through the genomics lens increases our understanding of the features of this a
Externí odkaz:
https://doaj.org/article/0868fe54848f4903803e6af94a2fabda
