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pro vyhledávání: '"Hero Alfred O."'
We revisit the problem of statistical sequence matching between two databases of sequences initiated by Unnikrishnan (TIT 2015) and derive theoretical performance guarantees for the generalized likelihood ratio test (GLRT). We first consider the case
Externí odkaz:
http://arxiv.org/abs/2407.02816
Autor:
Song, Dogyoon, Hero, Alfred O.
Multiway data analysis aims to uncover patterns in data structured as multi-indexed arrays, and the covariance of such data plays a crucial role in various machine learning applications. However, the intrinsically high dimension of multiway covarianc
Externí odkaz:
http://arxiv.org/abs/2302.02415
Autor:
Moon Kevin R., Li Jimmy J., Delouille Véronique, De Visscher Ruben, Watson Fraser, Hero Alfred O.
Publikováno v:
Journal of Space Weather and Space Climate, Vol 6, p A2 (2016)
Context. The flare productivity of an active region is observed to be related to its spatial complexity. Mount Wilson or McIntosh sunspot classifications measure such complexity but in a categorical way, and may therefore not use all the information
Externí odkaz:
https://doaj.org/article/46d3d0f563ec4a1e926e409d894f3581
Autor:
Robinson, Benjamin D., Malinas, Robert, Latimer, Van, Morrison, Beth Bjorkman, Hero, Alfred O.
Hotelling's $T^2$ test is a classical approach for discriminating the means of two multivariate normal samples that share a population covariance matrix. Hotelling's test is not ideal for high-dimensional samples because the eigenvalues of the estima
Externí odkaz:
http://arxiv.org/abs/2202.12725
Inference of community structure in probabilistic graphical models may not be consistent with fairness constraints when nodes have demographic attributes. Certain demographics may be over-represented in some detected communities and under-represented
Externí odkaz:
http://arxiv.org/abs/2112.05128
Autor:
Baranwal, Mayank, Saldinger, Jacob C., Kim, Doohyun, Elvati, Paolo, Hero, Alfred O., Violi, Angela
Publikováno v:
In Fuel 1 July 2024 367
The commonly used latent space embedding techniques, such as Principal Component Analysis, Factor Analysis, and manifold learning techniques, are typically used for learning effective representations of homogeneous data. However, they do not readily
Externí odkaz:
http://arxiv.org/abs/2108.12445
Many applications benefit from theory relevant to the identification of variables having large correlations or partial correlations in high dimension. Recently there has been progress in the ultra-high dimensional setting when the sample size $n$ is
Externí odkaz:
http://arxiv.org/abs/2101.04715
Network pruning in Convolutional Neural Networks (CNNs) has been extensively investigated in recent years. To determine the impact of pruning a group of filters on a network's accuracy, state-of-the-art pruning methods consistently assume filters of
Externí odkaz:
http://arxiv.org/abs/2009.05014
Autor:
She, Xichen, Zhai, Yaya, Henao, Ricardo, Woods, Christopher W., Chiu, Christopher, Ginsburg, Geoffrey S., Song, Peter X. K., Hero, Alfred O.
Publikováno v:
IEEE Transactions on Biomedical Engineering, Nov. 17 2020
$\textbf{Objective}$: To develop a multi-channel device event segmentation and feature extraction algorithm that is robust to changes in data distribution. $\textbf{Methods}$: We introduce an adaptive transfer learning algorithm to classify and segme
Externí odkaz:
http://arxiv.org/abs/2008.09215