Results 31 to 40 of about 384,953 (220)

$L_{1/2}$ Regularization: Convergence of Iterative Half Thresholding Algorithm

open access: yes, 2014
In recent studies on sparse modeling, the nonconvex regularization approaches (particularly, $L_{q}$ regularization with $q\in(0,1)$) have been demonstrated to possess capability of gaining much benefit in sparsity-inducing and efficiency.
Lin, Shaobo   +3 more
core   +1 more source

Regular factors in regular graphs

open access: yesDiscrete Mathematics, 1993
AbstractLet G be a k-regular, (k−1)-edge-connected graph with an even number of vertices, and let m be an integer such that1⩽m⩽k − 1. Then the graph obtained by removing any k − m edges of G, has an m-factor.
openaire   +2 more sources

Comparing self‐reported race and genetic ancestry for identifying potential differentially methylated sites in endometrial cancer: insights from African ancestry proportions using machine learning models

open access: yesMolecular Oncology, EarlyView.
Integrating ancestry, differential methylation analysis, and machine learning, we identified robust epigenetic signature genes (ESGs) and Core‐ESGs in Black and White women with endometrial cancer. Core‐ESGs (namely APOBEC1 and PLEKHG5) methylation levels were significantly associated with survival, with tumors from high African ancestry (THA) showing ...
Huma Asif, J. Julie Kim
wiley   +1 more source

Dimensional regularization of nonlinear sigma models on a finite time interval [PDF]

open access: yes, 2000
We extend dimensional regularization to the case of compact spaces. Contrary to previous regularization schemes employed for nonlinear sigma models on a finite time interval (``quantum mechanical path integrals in curved space'') dimensional ...
't Hooft   +25 more
core   +2 more sources

Beyond digital twins: the role of foundation models in enhancing the interpretability of multiomics modalities in precision medicine

open access: yesFEBS Open Bio, EarlyView.
This review highlights how foundation models enhance predictive healthcare by integrating advanced digital twin modeling with multiomics and biomedical data. This approach supports disease management, risk assessment, and personalized medicine, with the goal of optimizing health outcomes through adaptive, interpretable digital simulations, accessible ...
Sakhaa Alsaedi   +2 more
wiley   +1 more source

Dimensional Reduction and Hadronic Processes

open access: yes, 2008
We consider the application of regularization by dimensional reduction to NLO corrections of hadronic processes. The general collinear singularity structure is discussed, the origin of the regularization-scheme dependence is identified and transition ...
Adrian Signer   +3 more
core   +1 more source

Manifestly N=2 supersymmetric regularization for N=2 supersymmetric field theories [PDF]

open access: yes, 2015
We formulate the higher covariant derivative regularization for N=2 supersymmetric gauge theories in N=2 harmonic superspace. This regularization is constructed by adding the N=2 supersymmetric higher derivative term to the classical action and inserting
Buchbinder, I. L.   +2 more
core   +3 more sources

An approach for coherent periodogram averaging of tilt‐series data for improved contrast transfer function estimation

open access: yesFEBS Open Bio, EarlyView.
The contrast transfer function (CTF) is an imaging aberration that is a major resolution‐limiting factor in cryo‐electron microscopy (cryo‐EM). Precise CTF estimation is key to overcoming this limitation, but is particularly challenging in cryo‐electron tomography (cryo‐ET) data. Here, we present an approach for using geometric information to assist in
Sagar Khavnekar, William Wan
wiley   +1 more source

Regular factors in nearly regular graphs

open access: yesDiscrete Mathematics, 1984
AbstractWe strengthen classical theorems of Petersen, Ore, Bäbler, Gallai on the existence of regular factors in regular graphs to nearly regular graphs.
Bermond, Jean-Claude   +1 more
openaire   +3 more sources

A review of artificial intelligence in brachytherapy

open access: yesJournal of Applied Clinical Medical Physics, EarlyView.
Abstract Artificial intelligence (AI) has the potential to revolutionize brachytherapy's clinical workflow. This review comprehensively examines the application of AI, focusing on machine learning and deep learning, in various aspects of brachytherapy.
Jingchu Chen   +4 more
wiley   +1 more source

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