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pro vyhledávání: '"Gunderson, Lee M."'
Autor:
Watson, David S., Penn, Jordan, Gunderson, Lee M., Bravo-Hermsdorff, Gecia, Mastouri, Afsaneh, Silva, Ricardo
Publikováno v:
40th Conference on Uncertainty in Artificial Intelligence (UAI 2024)
Instrumental variables (IVs) are a popular and powerful tool for estimating causal effects in the presence of unobserved confounding. However, classical approaches rely on strong assumptions such as the $\textit{exclusion criterion}$, which states th
Externí odkaz:
http://arxiv.org/abs/2404.04446
Publikováno v:
NeurIPS 2023
In this work, we describe a method that determines an exact map from a finite set of subgraph densities to the parameters of a stochastic block model (SBM) matching these densities. Given a number $K$ of blocks, the subgraph densities of a finite num
Externí odkaz:
http://arxiv.org/abs/2402.00188
Autor:
Bravo-Hermsdorff, Gecia, Busa-Fekete, Robert, Gunderson, Lee M., Medina, Andrés Munõz, Syed, Umar
Data anonymization is an approach to privacy-preserving data release aimed at preventing participants reidentification, and it is an important alternative to differential privacy in applications that cannot tolerate noisy data. Existing algorithms fo
Externí odkaz:
http://arxiv.org/abs/2201.12306
Publikováno v:
Journal of Machine Learning Research (JMLR), 2023
How might one test the hypothesis that networks were sampled from the same distribution? Here, we compare two statistical tests that use subgraph counts to address this question. The first uses the empirical subgraph densities themselves as estimates
Externí odkaz:
http://arxiv.org/abs/2107.11403
Autor:
Bravo-Hermsdorff, Gecia, Felso, Valkyrie, Ray, Emily, Gunderson, Lee M., Helander, Mary E., Maria, Joana, Niv, Yael
Publikováno v:
Applied Network Science 4, 112 (2019)
One can point to a variety of historical milestones for gender equality in STEM (science, technology, engineering, and mathematics), however, practical effects are incremental and ongoing. It is important to quantify gender differences in subdomains
Externí odkaz:
http://arxiv.org/abs/2005.13512
In an increasingly interconnected world, understanding and summarizing the structure of these networks becomes increasingly relevant. However, this task is nontrivial; proposed summary statistics are as diverse as the networks they describe, and a st
Externí odkaz:
http://arxiv.org/abs/2002.03959
Publikováno v:
Advances in Neural Information Processing Systems 32 (NeurIPS 2019), pp. 7734-7746
How might one "reduce" a graph? That is, generate a smaller graph that preserves the global structure at the expense of discarding local details? There has been extensive work on both graph sparsification (removing edges) and graph coarsening (mergin
Externí odkaz:
http://arxiv.org/abs/1902.09702
Akademický článek
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Autor:
Gecia Bravo-Hermsdorff, Valkyrie Felso, Ray, Emily, Gunderson, Lee M., Helander, Mary E., Maria, Joana, Niv, Yael
Additional file 3 Gender ratios within individual INFORMS journals.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8c774744191f8cffaa672ed59169ec77