Results 41 to 50 of about 6,215,927 (306)

Local low-rank approach to nonlinear matrix completion

open access: yesEURASIP Journal on Advances in Signal Processing, 2021
This paper deals with a problem of matrix completion in which each column vector of the matrix belongs to a low-dimensional differentiable manifold (LDDM), with the target matrix being high or full rank.
Ryohei Sasaki   +3 more
doaj   +1 more source

On the Orbit Problem of Free Lie Algebras

open access: yesJournal of New Theory, 2023
By operationalizing $F_{n}$ as a free Lie Algebra of finite rank $n$, this work considers the orbit problem for $F_{n}$. The orbit problem is the following: given an element $u\in F_{n}$ and a finitely generated subalgebra $H$ of $F_{n}$, does $H$ meet ...
Zeynep Yaptı Özkurt
doaj   +1 more source

The Rank-Ramsey problem and the Log-Rank conjecture

open access: yesCombinatorics, Probability and Computing
Abstract A graph is called Rank-Ramsey if (i) Its clique number is small, and (ii) The adjacency matrix of its complement has small rank. We initiate a systematic study of such graphs. Our main motivation is that their constructions, as well as proofs of their non-existence, are intimately related to the famous ...
Gal Beniamini   +2 more
openaire   +2 more sources

Identifying Patterns of Hospitalizations Among Childhood Cancer Survivors: A Population‐Based Study

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Background Childhood cancer survivors (CCSs) experience more hospitalizations than the general population. We aimed to identify distinct hospitalization patterns among Queensland CCSs and the associated characteristics. Methods Cases (aged ≤14 years) diagnosed between 1995 and 2019 while residents of Queensland were identified through the ...
Hai Pham   +7 more
wiley   +1 more source

Low-Rank Representation-Based Object Tracking Using Multitask Feature Learning with Joint Sparsity

open access: yesAbstract and Applied Analysis, 2014
We address object tracking problem as a multitask feature learning process based on low-rank representation of features with joint sparsity. We first select features with low-rank representation within a number of initial frames to obtain subspace basis.
Hyuncheol Kim, Joonki Paik
doaj   +1 more source

Association Between Individualized Education for Kidney Replacement Therapy Modality Selection and Peritoneal Dialysis Initiation: A Cross‐Sectional Study

open access: yesTherapeutic Apheresis and Dialysis, EarlyView.
ABSTRACT Introduction Peritoneal dialysis (PD) is an established home‐based kidney replacement therapy (KRT), but its uptake remains low in Japan. We evaluated whether individualized education in a dedicated outpatient clinic was associated with the initiation of PD.
Yasuko Ito   +7 more
wiley   +1 more source

Algorithms and literate programs for weighted low-rank approximation with missing data

open access: yes, 2010
Linear models identification from data with missing values is posed as a weighted low-rank approximation problem with weights related to the missing values equal to zero.
Markovsky, Ivan, Ivan Markovsky
core   +1 more source

A Probabilistic Hyperspectral Imagery Restoration Method

open access: yesApplied Sciences, 2019
Hyperspectral image (HSI) restoration is an important task of hyperspectral imagery processing, which aims to improve the performance of the subsequent HSI interpretation and applications.
Wei Wei, Jiatao Nie, Chunna Tian
doaj   +1 more source

Organoids in pediatric cancer research

open access: yesFEBS Letters, EarlyView.
Organoid technology has revolutionized cancer research, yet its application in pediatric oncology remains limited. Recent advances have enabled the development of pediatric tumor organoids, offering new insights into disease biology, treatment response, and interactions with the tumor microenvironment.
Carla Ríos Arceo, Jarno Drost
wiley   +1 more source

Structured low-rank approximation and its applications

open access: yes, 2008
Fitting data by a bounded complexity linear model is equivalent to low-rank approximation of a matrix constructed from the data. The data matrix being Hankel structured is equivalent to the existence of a linear time-invariant system that fits the data ...
Markovsky, Ivan
core   +1 more source

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