Abstract: Semi-supervised symmetric non-negative matrix factorization (SNMF) utilizes the available supervisory information (usually in the form of pairwise constraints) to improve the clustering ...
1 Institute for Theoretical Physics, University of Bremen, Bremen, Germany 2 Institute of Electrodynamics and Microelectronics (ITEM.ids), University of Bremen, Bremen, Germany Considering biological ...
ABSTRACT: In this paper, an Optimal Predictive Modeling of Nonlinear Transformations “OPMNT” method has been developed while using Orthogonal Nonnegative Matrix Factorization “ONMF” with the ...
Tensor Extraction of Latent Features (T-ELF). Within T-ELF's arsenal are non-negative matrix and tensor factorization solutions, equipped with automatic model determination (also known as the ...
During a live event, Neal E. Ready, MD, and participants discussed use of PD-L1 status in non–small cell lung cancer and compared the use of single agent vs doublet immunotherapy in the PD-L1–low ...
As Machine Learning (ML) applications rapidly grow, concerns about adversarial attacks compromising their reliability have gained significant attention. One unsupervised ML method known for its ...
STADIUS Center for Dynamical Systems, Signal Processing, and Data Analytics, Department of Electrical Engineering (ESAT), KU Leuven, 3001 Leuven, Belgium ...
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